| { |
| "paper_id": "O16-1024", |
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| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T08:05:19.127494Z" |
| }, |
| "title": "Classification of Text Readability Based on Deep Neural Network and Representation Learning Techniques", |
| "authors": [ |
| { |
| "first": "Hou-Chiang", |
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| "institution": "National Taiwan Normal University", |
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| { |
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| "middle": [], |
| "last": "Tseng", |
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| "institution": "National Taiwan Normal University", |
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| { |
| "first": "Hsiao-Tsung", |
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| "last": "\u6d2a\u5b5d\u5b97", |
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| "institution": "Normal University", |
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| "country": "Taiwan" |
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| { |
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| "middle": [], |
| "last": "Hung", |
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| "institution": "Normal University", |
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| "country": "Taiwan" |
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| { |
| "first": "Yao-Ting", |
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| "institution": "Normal University", |
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| "country": "Taiwan" |
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| { |
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| "middle": [], |
| "last": "Sung", |
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| "institution": "Normal University", |
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| "country": "Taiwan" |
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| "email": "sungtc@ntnu.edu.tw" |
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| { |
| "first": "Berlin", |
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| "institution": "Normal University", |
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| "country": "Taiwan" |
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| "email": "berlin@ntnu.edu.tw" |
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| { |
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| "last": "Chen", |
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| "abstract": "The development of the internet has facilitated the flow of information. However, this explosive growth of information has led to fundamental importance being overlooked: Reading material can be understood. Research on readability formulas aims to predict, to a reasonable extent, the degree to which a text can be understood. It does so mainly by analyzing and translating the information within a text into readability features, which are used to train a readability model, in order to automatically predict the readability of a given text. In recent years, the development of deep neural networks, applied to speech recognition, image processing and natural language processing has improved significantly on the performance. Therefore, this paper proposes a readability model built with deep neural network and word vector representation, and which is capable of analyzing cross-domain texts, in accordance with the diverse topics of text contents. The authors aim to make the readability model capable of analyzing text readability with more accurate, as well as possess domain generalization capacity.", |
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| "text": "The development of the internet has facilitated the flow of information. However, this explosive growth of information has led to fundamental importance being overlooked: Reading material can be understood. Research on readability formulas aims to predict, to a reasonable extent, the degree to which a text can be understood. It does so mainly by analyzing and translating the information within a text into readability features, which are used to train a readability model, in order to automatically predict the readability of a given text. In recent years, the development of deep neural networks, applied to speech recognition, image processing and natural language processing has improved significantly on the performance. Therefore, this paper proposes a readability model built with deep neural network and word vector representation, and which is capable of analyzing cross-domain texts, in accordance with the diverse topics of text contents. The authors aim to make the readability model capable of analyzing text readability with more accurate, as well as possess domain generalization capacity.", |
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| "text": "\u53ef\u8b80\u6027(Readability)\u662f\u6307\u95b1\u8b80\u6750\u6599\u80fd\u5920\u88ab\u8b80\u8005\u7406\u89e3\u7684\u7a0b\u5ea6 [1] , [2] , [3] , [4] [9] , [10] , [11] [24] , [ ", |
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| "ref_id": "BIBREF8" |
| }, |
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| "ref_id": "BIBREF9" |
| }, |
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| "end": 72, |
| "text": "[11]", |
| "ref_id": "BIBREF10" |
| }, |
| { |
| "start": 73, |
| "end": 77, |
| "text": "[24]", |
| "ref_id": "BIBREF23" |
| }, |
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| "ref_id": null |
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| "text": "\u76ee \u524d \u5df2 \u6709 \u8a31 \u591a \u7814 \u7a76 \u6307 \u51fa \u50b3 \u7d71 \u53ef \u8b80 \u6027 \u516c \u5f0f \u4e26 \u4e0d \u9069 \u5408 \u8a55 \u91cf \u7db2 \u9801 \u6587 \u672c \u7684 \u53ef \u8b80 \u6027 [23],", |
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| "bib_entries": { |
| "BIBREF0": { |
| "ref_id": "b0", |
| "title": "The concept of readability", |
| "authors": [ |
| { |
| "first": "E", |
| "middle": [], |
| "last": "Dale", |
| "suffix": "" |
| }, |
| { |
| "first": "J", |
| "middle": [ |
| "S" |
| ], |
| "last": "Chall", |
| "suffix": "" |
| } |
| ], |
| "year": 1949, |
| "venue": "Elementary English", |
| "volume": "26", |
| "issue": "", |
| "pages": "19--26", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "E. Dale and J. S. Chall, \"The concept of readability,\" Elementary English, vol. 26, pp. 19- 26, 1949.", |
| "links": null |
| }, |
| "BIBREF1": { |
| "ref_id": "b1", |
| "title": "Measurement of Readability", |
| "authors": [ |
| { |
| "first": "G", |
| "middle": [ |
| "R" |
| ], |
| "last": "Klare", |
| "suffix": "" |
| } |
| ], |
| "year": 1963, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "G. R. Klare, Measurement of Readability, 1963.", |
| "links": null |
| }, |
| "BIBREF2": { |
| "ref_id": "b2", |
| "title": "The measurement of readability: useful information for communicators", |
| "authors": [ |
| { |
| "first": "G", |
| "middle": [ |
| "R" |
| ], |
| "last": "Klare", |
| "suffix": "" |
| } |
| ], |
| "year": 2000, |
| "venue": "ACM Journal of Computer Documentation (JCD)", |
| "volume": "24", |
| "issue": "", |
| "pages": "107--121", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "G. R. Klare, \"The measurement of readability: useful information for communicators,\" ACM Journal of Computer Documentation (JCD), vol. 24, pp. 107-121, 2000.", |
| "links": null |
| }, |
| "BIBREF3": { |
| "ref_id": "b3", |
| "title": "SMOG grading: A new readability formula", |
| "authors": [ |
| { |
| "first": "G", |
| "middle": [ |
| "H" |
| ], |
| "last": "Mclaughlin", |
| "suffix": "" |
| } |
| ], |
| "year": 1969, |
| "venue": "Journal of reading", |
| "volume": "12", |
| "issue": "", |
| "pages": "639--646", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "G. H. McLaughlin, \"SMOG grading: A new readability formula,\" Journal of reading, vol. 12, pp. 639-646, 1969.", |
| "links": null |
| }, |
| "BIBREF4": { |
| "ref_id": "b4", |
| "title": "A method for measuring the vocabulary burden of textbooks", |
| "authors": [ |
| { |
| "first": "B", |
| "middle": [ |
| "A" |
| ], |
| "last": "Lively", |
| "suffix": "" |
| }, |
| { |
| "first": "S", |
| "middle": [ |
| "L" |
| ], |
| "last": "Pressey", |
| "suffix": "" |
| } |
| ], |
| "year": 1923, |
| "venue": "Educational administration and supervision", |
| "volume": "9", |
| "issue": "", |
| "pages": "389--398", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "B. A. Lively and S. L. Pressey, \"A method for measuring the vocabulary burden of textbooks,\" Educational administration and supervision, vol. 9, pp. 389-398, 1923.", |
| "links": null |
| }, |
| "BIBREF5": { |
| "ref_id": "b5", |
| "title": "An objective method of determining grade placement of children's reading material", |
| "authors": [ |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Vogel", |
| "suffix": "" |
| }, |
| { |
| "first": "C", |
| "middle": [], |
| "last": "Washburne", |
| "suffix": "" |
| } |
| ], |
| "year": 1928, |
| "venue": "The Elementary School Journal", |
| "volume": "", |
| "issue": "", |
| "pages": "373--381", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "M. Vogel and C. Washburne, \"An objective method of determining grade placement of children's reading material,\" The Elementary School Journal, pp. 373-381, 1928.", |
| "links": null |
| }, |
| "BIBREF6": { |
| "ref_id": "b6", |
| "title": "Readability Revisited: The new Dale-Chall Readability Formula", |
| "authors": [ |
| { |
| "first": "J", |
| "middle": [ |
| "S" |
| ], |
| "last": "Chall", |
| "suffix": "" |
| }, |
| { |
| "first": "E", |
| "middle": [], |
| "last": "Dale", |
| "suffix": "" |
| } |
| ], |
| "year": 1995, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "J. S. Chall and E. Dale, Readability Revisited: The new Dale-Chall Readability Formula, Brookline Books, 1995.", |
| "links": null |
| }, |
| "BIBREF7": { |
| "ref_id": "b7", |
| "title": "A new readability yardstick", |
| "authors": [ |
| { |
| "first": "R", |
| "middle": [], |
| "last": "Flesch", |
| "suffix": "" |
| } |
| ], |
| "year": 1948, |
| "venue": "Journal of applied psychology", |
| "volume": "32", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "R. Flesch, \"A new readability yardstick,\" Journal of applied psychology, vol. 32, p. 221, 1948.", |
| "links": null |
| }, |
| "BIBREF8": { |
| "ref_id": "b8", |
| "title": "A machine learning approach to reading level assessment", |
| "authors": [ |
| { |
| "first": "S", |
| "middle": [ |
| "E" |
| ], |
| "last": "Petersen", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Ostendorf", |
| "suffix": "" |
| } |
| ], |
| "year": 2009, |
| "venue": "Computer Speech & Language", |
| "volume": "23", |
| "issue": "", |
| "pages": "89--106", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "S. E. Petersen and M. Ostendorf, \"A machine learning approach to reading level assessment,\" Computer Speech & Language, vol. 23, pp. 89-106, 2009.", |
| "links": null |
| }, |
| "BIBREF9": { |
| "ref_id": "b9", |
| "title": "A comparison of features for automatic readability assessment", |
| "authors": [ |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Feng", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Jansche", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Huenerfauth", |
| "suffix": "" |
| }, |
| { |
| "first": "N", |
| "middle": [], |
| "last": "Elhadad", |
| "suffix": "" |
| } |
| ], |
| "year": 2010, |
| "venue": "Proceedings of the 23rd International Conference on Computational Linguistics: Posters", |
| "volume": "", |
| "issue": "", |
| "pages": "276--284", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "L. Feng, M. Jansche, M. Huenerfauth, and N. Elhadad, \"A comparison of features for automatic readability assessment,\" in Proceedings of the 23rd International Conference on Computational Linguistics: Posters, 2010, pp. 276-284.", |
| "links": null |
| }, |
| "BIBREF10": { |
| "ref_id": "b10", |
| "title": "Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning", |
| "authors": [ |
| { |
| "first": "Y.-T", |
| "middle": [], |
| "last": "Sung", |
| "suffix": "" |
| }, |
| { |
| "first": "J.-L", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "J.-H", |
| "middle": [], |
| "last": "Cha", |
| "suffix": "" |
| }, |
| { |
| "first": "H.-C", |
| "middle": [], |
| "last": "Tseng", |
| "suffix": "" |
| }, |
| { |
| "first": "T.-H", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "" |
| }, |
| { |
| "first": "K.-E", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "" |
| } |
| ], |
| "year": 2014, |
| "venue": "Behavior research methods", |
| "volume": "47", |
| "issue": "", |
| "pages": "340--354", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Y.-T. Sung, J.-L. Chen, J.-H. Cha, H.-C. Tseng, T.-H. Chang, and K.-E. Chang, \"Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning,\" Behavior research methods, vol. 47, pp. 340- 354, 2014.", |
| "links": null |
| }, |
| "BIBREF11": { |
| "ref_id": "b11", |
| "title": "Constructing inferences during narrative text comprehension", |
| "authors": [ |
| { |
| "first": "A", |
| "middle": [ |
| "C" |
| ], |
| "last": "Graesser", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Singer", |
| "suffix": "" |
| }, |
| { |
| "first": "T", |
| "middle": [], |
| "last": "Trabasso", |
| "suffix": "" |
| } |
| ], |
| "year": 1994, |
| "venue": "Psychological Review", |
| "volume": "101", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "A. C. Graesser, M. Singer, and T. Trabasso, \"Constructing inferences during narrative text comprehension,\" Psychological Review, vol. 101, p. 371, 1994.", |
| "links": null |
| }, |
| "BIBREF12": { |
| "ref_id": "b12", |
| "title": "Computational assessment of text readability: A survey of current and future research", |
| "authors": [ |
| { |
| "first": "K", |
| "middle": [], |
| "last": "Collins-Thompson", |
| "suffix": "" |
| } |
| ], |
| "year": 2014, |
| "venue": "International Journal of Applied Linguistics", |
| "volume": "165", |
| "issue": "", |
| "pages": "97--135", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "K. Collins-Thompson, \"Computational assessment of text readability: A survey of current and future research,\" International Journal of Applied Linguistics, vol. 165, pp. 97-135, 2014.", |
| "links": null |
| }, |
| "BIBREF13": { |
| "ref_id": "b13", |
| "title": "Concept-based document readability in domain specific information retrieval", |
| "authors": [ |
| { |
| "first": "X", |
| "middle": [], |
| "last": "Yan", |
| "suffix": "" |
| }, |
| { |
| "first": "D", |
| "middle": [], |
| "last": "Song", |
| "suffix": "" |
| }, |
| { |
| "first": "X", |
| "middle": [], |
| "last": "Li", |
| "suffix": "" |
| } |
| ], |
| "year": 2006, |
| "venue": "Proceedings of the 15th ACM international conference on Information and knowledge management", |
| "volume": "", |
| "issue": "", |
| "pages": "540--549", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "X. Yan, D. Song, and X. Li, \"Concept-based document readability in domain specific information retrieval,\" in Proceedings of the 15th ACM international conference on Information and knowledge management, 2006, pp. 540-549.", |
| "links": null |
| }, |
| "BIBREF14": { |
| "ref_id": "b14", |
| "title": "Lexically based distinction of readability levels of health documents", |
| "authors": [ |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Borst", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Gaudinat", |
| "suffix": "" |
| }, |
| { |
| "first": "C", |
| "middle": [], |
| "last": "Boyer", |
| "suffix": "" |
| }, |
| { |
| "first": "N", |
| "middle": [], |
| "last": "Grabar", |
| "suffix": "" |
| } |
| ], |
| "year": 2008, |
| "venue": "Acta Informatica Medica", |
| "volume": "16", |
| "issue": "", |
| "pages": "72--75", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "A. Borst, A. Gaudinat, C. Boyer, and N. Grabar, \"Lexically based distinction of readability levels of health documents,\" Acta Informatica Medica, vol. 16, pp. 72-75, 2008.", |
| "links": null |
| }, |
| "BIBREF15": { |
| "ref_id": "b15", |
| "title": "Evaluating the difficulty of concepts on domain knowledge using latent semantic analysis", |
| "authors": [ |
| { |
| "first": "T.-H", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "" |
| }, |
| { |
| "first": "Y.-T", |
| "middle": [], |
| "last": "Sung", |
| "suffix": "" |
| }, |
| { |
| "first": "Y.-T", |
| "middle": [], |
| "last": "Lee", |
| "suffix": "" |
| } |
| ], |
| "year": 2013, |
| "venue": "Proceedings of the International Conference on Asian Language Processing (IALP)", |
| "volume": "", |
| "issue": "", |
| "pages": "193--196", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "T.-H. Chang, Y.-T. Sung, and Y.-T. Lee, \"Evaluating the difficulty of concepts on domain knowledge using latent semantic analysis,\" in Proceedings of the International Conference on Asian Language Processing (IALP), pp. 193-196, 2013", |
| "links": null |
| }, |
| "BIBREF16": { |
| "ref_id": "b16", |
| "title": "Readability Test", |
| "authors": [], |
| "year": 2015, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "[17] Juicy Studio. (2015). Readability Test. Retrieved from http://juicystudio.com/services/readability.php.", |
| "links": null |
| }, |
| "BIBREF17": { |
| "ref_id": "b17", |
| "title": "The Readability Test Tool", |
| "authors": [ |
| { |
| "first": "David", |
| "middle": [], |
| "last": "Simpson", |
| "suffix": "" |
| } |
| ], |
| "year": 2015, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "David Simpson. (2015). The Readability Test Tool. Retrieved from http://read-able.com/.", |
| "links": null |
| }, |
| "BIBREF18": { |
| "ref_id": "b18", |
| "title": "Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel", |
| "authors": [ |
| { |
| "first": "J", |
| "middle": [ |
| "P" |
| ], |
| "last": "Kincaid", |
| "suffix": "" |
| }, |
| { |
| "first": "R", |
| "middle": [ |
| "P" |
| ], |
| "last": "Fishburne", |
| "suffix": "" |
| }, |
| { |
| "first": "R", |
| "middle": [ |
| "L" |
| ], |
| "last": "Rogers", |
| "suffix": "" |
| }, |
| { |
| "first": "B", |
| "middle": [ |
| "S" |
| ], |
| "last": "Chissom", |
| "suffix": "" |
| } |
| ], |
| "year": 1975, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "J. P. Kincaid, R. P. Fishburne Jr, R. L. Rogers, and B. S. Chissom, \"Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel,\" DTIC Document, 1975.", |
| "links": null |
| }, |
| "BIBREF19": { |
| "ref_id": "b19", |
| "title": "The Technique of Clear Writing", |
| "authors": [ |
| { |
| "first": "R", |
| "middle": [], |
| "last": "Gunning", |
| "suffix": "" |
| } |
| ], |
| "year": 1952, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "R. Gunning, The Technique of Clear Writing, 1952.", |
| "links": null |
| }, |
| "BIBREF20": { |
| "ref_id": "b20", |
| "title": "The linguistic assumptions underlying readability formulae: A critique", |
| "authors": [ |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Bailin", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Grafstein", |
| "suffix": "" |
| } |
| ], |
| "year": 2001, |
| "venue": "Language & Communication", |
| "volume": "21", |
| "issue": "", |
| "pages": "285--301", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "A. Bailin and A. Grafstein, \"The linguistic assumptions underlying readability formulae: A critique,\" Language & Communication, vol. 21, pp. 285-301, 2001.", |
| "links": null |
| }, |
| "BIBREF21": { |
| "ref_id": "b21", |
| "title": "Statistical estimation of word acquisition with application to readability prediction", |
| "authors": [ |
| { |
| "first": "P", |
| "middle": [], |
| "last": "Kidwell", |
| "suffix": "" |
| }, |
| { |
| "first": "G", |
| "middle": [], |
| "last": "Lebanon", |
| "suffix": "" |
| }, |
| { |
| "first": "K", |
| "middle": [], |
| "last": "Collins-Thompson", |
| "suffix": "" |
| } |
| ], |
| "year": 2011, |
| "venue": "Journal of the American Statistical Association", |
| "volume": "106", |
| "issue": "", |
| "pages": "21--30", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "P. Kidwell, G. Lebanon, and K. Collins-Thompson, \"Statistical estimation of word acquisition with application to readability prediction,\" Journal of the American Statistical Association, vol. 106, pp. 21-30, 2011.", |
| "links": null |
| }, |
| "BIBREF22": { |
| "ref_id": "b22", |
| "title": "A statistical model for scientific readability", |
| "authors": [ |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Si", |
| "suffix": "" |
| }, |
| { |
| "first": "J", |
| "middle": [], |
| "last": "Callan", |
| "suffix": "" |
| } |
| ], |
| "year": 2001, |
| "venue": "Proceedings of the International Conference on Information and Knowledge Management", |
| "volume": "", |
| "issue": "", |
| "pages": "574--576", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "L. Si and J. Callan, \"A statistical model for scientific readability,\" in Proceedings of the International Conference on Information and Knowledge Management, pp. 574-576, 2001.", |
| "links": null |
| }, |
| "BIBREF23": { |
| "ref_id": "b23", |
| "title": "A language modeling approach to predicting reading difficulty", |
| "authors": [ |
| { |
| "first": "K", |
| "middle": [], |
| "last": "Collins-Thompson", |
| "suffix": "" |
| }, |
| { |
| "first": "J", |
| "middle": [ |
| "P" |
| ], |
| "last": "Callan", |
| "suffix": "" |
| } |
| ], |
| "year": 2004, |
| "venue": "Proceedings of HLT-NAACL", |
| "volume": "", |
| "issue": "", |
| "pages": "193--200", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "K. Collins-Thompson and J. P. Callan, \"A language modeling approach to predicting reading difficulty,\" in Proceedings of HLT-NAACL, pp. 193-200, 2004.", |
| "links": null |
| }, |
| "BIBREF24": { |
| "ref_id": "b24", |
| "title": "Cognitively motivated features for readability assessment", |
| "authors": [ |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Feng", |
| "suffix": "" |
| }, |
| { |
| "first": "N", |
| "middle": [], |
| "last": "Elhadad", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Huenerfauth", |
| "suffix": "" |
| } |
| ], |
| "year": 2009, |
| "venue": "Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics", |
| "volume": "", |
| "issue": "", |
| "pages": "229--237", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "L. Feng, N. Elhadad, and M. Huenerfauth, \"Cognitively motivated features for readability assessment,\" in Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics, pp. 229-237, 2009.", |
| "links": null |
| }, |
| "BIBREF25": { |
| "ref_id": "b25", |
| "title": "Read-x: Automatic evaluation of reading difficulty of web text", |
| "authors": [ |
| { |
| "first": "E", |
| "middle": [], |
| "last": "Miltsakaki", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Troutt", |
| "suffix": "" |
| } |
| ], |
| "year": 2007, |
| "venue": "Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education", |
| "volume": "", |
| "issue": "", |
| "pages": "7280--7286", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "E. Miltsakaki and A. Troutt, \"Read-x: Automatic evaluation of reading difficulty of web text,\" in Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 7280-7286, 2007.", |
| "links": null |
| }, |
| "BIBREF26": { |
| "ref_id": "b26", |
| "title": "Real-time web text classification and analysis of reading difficulty", |
| "authors": [ |
| { |
| "first": "E", |
| "middle": [], |
| "last": "Miltsakaki", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Troutt", |
| "suffix": "" |
| } |
| ], |
| "year": 2008, |
| "venue": "Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications", |
| "volume": "", |
| "issue": "", |
| "pages": "89--97", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "E. Miltsakaki and A. Troutt, \"Real-time web text classification and analysis of reading difficulty,\" in Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications, 2008, pp. 89-97.", |
| "links": null |
| }, |
| "BIBREF27": { |
| "ref_id": "b27", |
| "title": "Matching readers' preferences and reading skills with appropriate web texts", |
| "authors": [ |
| { |
| "first": "E", |
| "middle": [], |
| "last": "Miltsakaki", |
| "suffix": "" |
| } |
| ], |
| "year": 2009, |
| "venue": "Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session", |
| "volume": "", |
| "issue": "", |
| "pages": "49--52", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "E. Miltsakaki, \"Matching readers' preferences and reading skills with appropriate web texts,\" in Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations Session, pp. 49-52, 2009.", |
| "links": null |
| }, |
| "BIBREF28": { |
| "ref_id": "b28", |
| "title": "Web page classification on child suitability", |
| "authors": [ |
| { |
| "first": "C", |
| "middle": [], |
| "last": "Eickhoff", |
| "suffix": "" |
| }, |
| { |
| "first": "P", |
| "middle": [], |
| "last": "Serdyukov", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [ |
| "P" |
| ], |
| "last": "De Vries", |
| "suffix": "" |
| } |
| ], |
| "year": 2010, |
| "venue": "Proceedings of the ACM International Conference on Information and Knowledge Management", |
| "volume": "", |
| "issue": "", |
| "pages": "1425--1428", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "C. Eickhoff, P. Serdyukov, and A. P. de Vries, \"Web page classification on child suitability,\" in Proceedings of the ACM International Conference on Information and Knowledge Management, pp. 1425-1428, 2010.", |
| "links": null |
| }, |
| "BIBREF29": { |
| "ref_id": "b29", |
| "title": "Predicting the readability of short web summaries", |
| "authors": [ |
| { |
| "first": "T", |
| "middle": [], |
| "last": "Kanungo", |
| "suffix": "" |
| }, |
| { |
| "first": "D", |
| "middle": [], |
| "last": "Orr", |
| "suffix": "" |
| } |
| ], |
| "year": 2009, |
| "venue": "Proceedings of the ACM International Conference on Web Search and Data Mining", |
| "volume": "", |
| "issue": "", |
| "pages": "202--211", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "T. Kanungo and D. Orr, \"Predicting the readability of short web summaries,\" in Proceedings of the ACM International Conference on Web Search and Data Mining, pp. 202-211, 2009.", |
| "links": null |
| }, |
| "BIBREF30": { |
| "ref_id": "b30", |
| "title": "A machine learning approach to reading level assessment", |
| "authors": [ |
| { |
| "first": "S", |
| "middle": [], |
| "last": "Petersen", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Ostendorf", |
| "suffix": "" |
| } |
| ], |
| "year": 2009, |
| "venue": "Computer Speech & Language", |
| "volume": "23", |
| "issue": "1", |
| "pages": "89--106", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "S. Petersen and M. Ostendorf, \"A machine learning approach to reading level assessment,\" Computer Speech & Language, vol. 23, no. 1, pp. 89-106, 2009.", |
| "links": null |
| }, |
| "BIBREF31": { |
| "ref_id": "b31", |
| "title": "A comparison of features for automatic readability assessment", |
| "authors": [ |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Feng", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Jansche", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Huenerfauth", |
| "suffix": "" |
| }, |
| { |
| "first": "N", |
| "middle": [], |
| "last": "Elhadad", |
| "suffix": "" |
| } |
| ], |
| "year": 2010, |
| "venue": "Proceedings of the International Conference on Computational Linguistics: Posters. Association for Computational Linguistics", |
| "volume": "", |
| "issue": "", |
| "pages": "276--284", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "L. Feng, M. Jansche, M. Huenerfauth, and N. Elhadad, \"A comparison of features for automatic readability assessment,\" In Proceedings of the International Conference on Computational Linguistics: Posters. Association for Computational Linguistics, pp. 276- 284, 2010.", |
| "links": null |
| }, |
| "BIBREF32": { |
| "ref_id": "b32", |
| "title": "Do NLP and machine learning improve traditional readability formulas?", |
| "authors": [ |
| { |
| "first": "T", |
| "middle": [], |
| "last": "Fran\u00e7ois", |
| "suffix": "" |
| }, |
| { |
| "first": "E", |
| "middle": [], |
| "last": "Miltsakaki", |
| "suffix": "" |
| } |
| ], |
| "year": 2012, |
| "venue": "Proceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations", |
| "volume": "", |
| "issue": "", |
| "pages": "49--57", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "T. Fran\u00e7ois and E. Miltsakaki, \"Do NLP and machine learning improve traditional readability formulas?,\" in Proceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations. Association for Computational Linguistics, pp. 49-57, 2012.", |
| "links": null |
| }, |
| "BIBREF33": { |
| "ref_id": "b33", |
| "title": "Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning", |
| "authors": [ |
| { |
| "first": "Y", |
| "middle": [], |
| "last": "Sung", |
| "suffix": "" |
| }, |
| { |
| "first": "J", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "J", |
| "middle": [], |
| "last": "Cha", |
| "suffix": "" |
| }, |
| { |
| "first": "H", |
| "middle": [], |
| "last": "Tseng", |
| "suffix": "" |
| }, |
| { |
| "first": "T", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "" |
| }, |
| { |
| "first": "K", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "" |
| } |
| ], |
| "year": 2014, |
| "venue": "Behavior research methods", |
| "volume": "47", |
| "issue": "2", |
| "pages": "340--354", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Y. Sung, J. Chen, J. Cha, H. Tseng, T. Chang and K. Chang, \"Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning,\" Behavior research methods, vol. 47, no. 2, pp. 340-354, 2014.", |
| "links": null |
| }, |
| "BIBREF34": { |
| "ref_id": "b34", |
| "title": "Foundations and Trends in Signal Processing", |
| "authors": [ |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Deng", |
| "suffix": "" |
| }, |
| { |
| "first": "D", |
| "middle": [], |
| "last": "Yu", |
| "suffix": "" |
| } |
| ], |
| "year": 2014, |
| "venue": "", |
| "volume": "7", |
| "issue": "", |
| "pages": "197--387", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "L. Deng, and D. Yu, \"Deep Learning Methods and Applications,\" vol. 7, no. 3-4, pp 197-387, Foundations and Trends in Signal Processing, 2014.", |
| "links": null |
| }, |
| "BIBREF35": { |
| "ref_id": "b35", |
| "title": "Learning distributed representations of concepts", |
| "authors": [ |
| { |
| "first": "G", |
| "middle": [ |
| "E" |
| ], |
| "last": "Hinton", |
| "suffix": "" |
| } |
| ], |
| "year": 1986, |
| "venue": "Proceedings of the Annual Conference of the Cognitive Science Society", |
| "volume": "", |
| "issue": "", |
| "pages": "1--12", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "G. E. Hinton, \"Learning distributed representations of concepts,\" in Proceedings of the Annual Conference of the Cognitive Science Society, pp. 1-12, 1986.", |
| "links": null |
| }, |
| "BIBREF36": { |
| "ref_id": "b36", |
| "title": "A neural probabilistic language model", |
| "authors": [ |
| { |
| "first": "Y", |
| "middle": [], |
| "last": "Bengio", |
| "suffix": "" |
| }, |
| { |
| "first": "R", |
| "middle": [], |
| "last": "Ducharme", |
| "suffix": "" |
| }, |
| { |
| "first": "P", |
| "middle": [], |
| "last": "Vincent", |
| "suffix": "" |
| }, |
| { |
| "first": "C", |
| "middle": [], |
| "last": "Janvin", |
| "suffix": "" |
| } |
| ], |
| "year": 2003, |
| "venue": "The Journal of Machine Learning Research", |
| "volume": "3", |
| "issue": "", |
| "pages": "1137--1155", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Y. Bengio, R. Ducharme, P. Vincent, and C. Janvin, \"A neural probabilistic language model,\" The Journal of Machine Learning Research, vol. 3, pp. 1137-1155, 2003.", |
| "links": null |
| }, |
| "BIBREF37": { |
| "ref_id": "b37", |
| "title": "Efficient estimation of word representations in vector space", |
| "authors": [ |
| { |
| "first": "T", |
| "middle": [], |
| "last": "Mikolov", |
| "suffix": "" |
| }, |
| { |
| "first": "K", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "G", |
| "middle": [], |
| "last": "Corrado", |
| "suffix": "" |
| }, |
| { |
| "first": "J", |
| "middle": [], |
| "last": "Dean", |
| "suffix": "" |
| } |
| ], |
| "year": 2013, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": { |
| "arXiv": [ |
| "arXiv:1301.3781" |
| ] |
| }, |
| "num": null, |
| "urls": [], |
| "raw_text": "T. Mikolov, K. Chen, G. Corrado, and J. Dean, \"Efficient estimation of word representations in vector space,\" arXiv preprint arXiv:1301.3781, 2013.", |
| "links": null |
| }, |
| "BIBREF38": { |
| "ref_id": "b38", |
| "title": "Glove: Global vectors for word representation", |
| "authors": [ |
| { |
| "first": "J", |
| "middle": [], |
| "last": "Pennington", |
| "suffix": "" |
| }, |
| { |
| "first": "R", |
| "middle": [], |
| "last": "Socher", |
| "suffix": "" |
| }, |
| { |
| "first": "C", |
| "middle": [ |
| "D" |
| ], |
| "last": "Manning", |
| "suffix": "" |
| } |
| ], |
| "year": 2014, |
| "venue": "Proceedings of the Empirical Methods in Natural Language Processing", |
| "volume": "12", |
| "issue": "", |
| "pages": "1532--1543", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "J. Pennington, R. Socher, and C. D. Manning, \"Glove: Global vectors for word representation,\" in Proceedings of the Empirical Methods in Natural Language Processing, vol. 12, pp. 1532-1543, 2014.", |
| "links": null |
| }, |
| "BIBREF39": { |
| "ref_id": "b39", |
| "title": "Classification of text readability based on representation learning techniques", |
| "authors": [ |
| { |
| "first": "H", |
| "middle": [ |
| "C" |
| ], |
| "last": "Tseng", |
| "suffix": "" |
| }, |
| { |
| "first": "Y", |
| "middle": [ |
| "T" |
| ], |
| "last": "Sung", |
| "suffix": "" |
| }, |
| { |
| "first": "B", |
| "middle": [], |
| "last": "Chen", |
| "suffix": "" |
| }, |
| { |
| "first": "W", |
| "middle": [ |
| "E" |
| ], |
| "last": "Lee", |
| "suffix": "" |
| } |
| ], |
| "year": 2016, |
| "venue": "Proceedings of the Annual Meeting of the Society for Text & Discourse, kassel", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "H. C. Tseng, Y. T. Sung, B. Chen, W. E. Lee, \"Classification of text readability based on representation learning techniques,\" in Proceedings of the Annual Meeting of the Society for Text & Discourse, kassel, 2016.", |
| "links": null |
| }, |
| "BIBREF40": { |
| "ref_id": "b40", |
| "title": "Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups", |
| "authors": [ |
| { |
| "first": "G", |
| "middle": [], |
| "last": "Hinton", |
| "suffix": "" |
| }, |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Deng", |
| "suffix": "" |
| }, |
| { |
| "first": "D", |
| "middle": [], |
| "last": "Yu", |
| "suffix": "" |
| }, |
| { |
| "first": "G", |
| "middle": [ |
| "E" |
| ], |
| "last": "Dahl", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Mohamed", |
| "suffix": "" |
| }, |
| { |
| "first": "N", |
| "middle": [], |
| "last": "Jaitly", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Senior", |
| "suffix": "" |
| }, |
| { |
| "first": "V", |
| "middle": [], |
| "last": "Vanhoucke", |
| "suffix": "" |
| }, |
| { |
| "first": "P", |
| "middle": [], |
| "last": "Nguyen", |
| "suffix": "" |
| }, |
| { |
| "first": "T", |
| "middle": [ |
| "N" |
| ], |
| "last": "Sainath", |
| "suffix": "" |
| } |
| ], |
| "year": 2012, |
| "venue": "IEEE Signal Processing Magazine", |
| "volume": "29", |
| "issue": "", |
| "pages": "82--97", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "G. Hinton, L. Deng, D. Yu, G. E. Dahl, A.-r. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, and T. N. Sainath, \"Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,\" IEEE Signal Processing Magazine, vol. 29, pp. 82-97, 2012.", |
| "links": null |
| }, |
| "BIBREF41": { |
| "ref_id": "b41", |
| "title": "Rectified linear units improve restricted boltzmann machines", |
| "authors": [ |
| { |
| "first": "Vinod", |
| "middle": [], |
| "last": "Nair", |
| "suffix": "" |
| }, |
| { |
| "first": "Geoffrey", |
| "middle": [ |
| "E" |
| ], |
| "last": "Hinton", |
| "suffix": "" |
| } |
| ], |
| "year": 2010, |
| "venue": "Proceedings of the International Conference on Machine Learning", |
| "volume": "", |
| "issue": "", |
| "pages": "807--814", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Nair, Vinod, and Geoffrey E. Hinton. \"Rectified linear units improve restricted boltzmann machines,\" in Proceedings of the International Conference on Machine Learning, pp. 807-814. 2010.", |
| "links": null |
| }, |
| "BIBREF42": { |
| "ref_id": "b42", |
| "title": "A Chinese word segmentation and POS tagging system for readability research", |
| "authors": [ |
| { |
| "first": "T", |
| "middle": [ |
| "H" |
| ], |
| "last": "Chang", |
| "suffix": "" |
| }, |
| { |
| "first": "Y", |
| "middle": [ |
| "T" |
| ], |
| "last": "Sung", |
| "suffix": "" |
| }, |
| { |
| "first": "Y", |
| "middle": [ |
| "T" |
| ], |
| "last": "Lee", |
| "suffix": "" |
| } |
| ], |
| "year": 2012, |
| "venue": "Proceedings of the Annual Meeting of the Society for Computers in Psychology", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "T. H. Chang, Y. T. Sung, and Y. T. Lee, \"A Chinese word segmentation and POS tagging system for readability research.\" in Proceedings of the Annual Meeting of the Society for Computers in Psychology, 2012.", |
| "links": null |
| }, |
| "BIBREF43": { |
| "ref_id": "b43", |
| "title": "Keras", |
| "authors": [], |
| "year": null, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "\"Keras\", Available at: https://github.com/fchollet/keras.", |
| "links": null |
| }, |
| "BIBREF44": { |
| "ref_id": "b44", |
| "title": "LIBSVM: A library for support vector machines", |
| "authors": [ |
| { |
| "first": "C.-C", |
| "middle": [], |
| "last": "Chang", |
| "suffix": "" |
| }, |
| { |
| "first": "C.-J", |
| "middle": [], |
| "last": "Lin", |
| "suffix": "" |
| } |
| ], |
| "year": 2011, |
| "venue": "ACM Transactions on Intelligent Systems and Technology", |
| "volume": "2", |
| "issue": "", |
| "pages": "1--27", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "C.-C. Chang and C.-J. Lin, \"LIBSVM: A library for support vector machines,\" ACM Transactions on Intelligent Systems and Technology, vol. 2, pp. 27:1-27, 2011.", |
| "links": null |
| }, |
| "BIBREF45": { |
| "ref_id": "b45", |
| "title": "Distributed representations of sentences and documents", |
| "authors": [ |
| { |
| "first": "Q", |
| "middle": [ |
| "V" |
| ], |
| "last": "Le", |
| "suffix": "" |
| }, |
| { |
| "first": "T", |
| "middle": [], |
| "last": "Mikolov", |
| "suffix": "" |
| } |
| ], |
| "year": 2014, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": { |
| "arXiv": [ |
| "arXiv:1405.4053" |
| ] |
| }, |
| "num": null, |
| "urls": [], |
| "raw_text": "Q. V. Le and T. Mikolov, \"Distributed representations of sentences and documents,\" arXiv preprint arXiv:1405.4053, 2014.", |
| "links": null |
| } |
| }, |
| "ref_entries": { |
| "TABREF0": { |
| "content": "<table/>", |
| "num": null, |
| "type_str": "table", |
| "html": null, |
| "text": "\uff0c\u7576\u8b80\u8005\u95b1\u8b80\u9ad8\u53ef \u8b80\u6027\u7684\u6587\u4ef6\u6642\uff0c\u6703\u7522\u751f\u8f03\u597d\u7684\u7406\u89e3\u53ca\u5b78\u5f8c\u4fdd\u7559\u6548\u679c[2],[3]\u3002\u7531\u65bc\u6587\u4ef6\u7684\u53ef\u8b80\u6027\u662f\u5982\u6b64\u91cd \u8981\uff0c\u56e0\u6b64\u65e9\u5728 1923 \u5e74 Lively \u548c Pressey \u5c31\u63d0\u51fa\u65b9\u6cd5\u4f86\u63a2\u8a0e\u6559\u79d1\u66f8\u4e2d\u5b57\u5f59\u96e3\u5ea6\u7684\u554f\u984c[5]\u3002 \u5728 1928 \u5e74 Vogel \u548c Washburne \u5247\u662f\u63d0\u51fa\u4e00\u500b Winnetka Formula \u4f86\u8a55\u91cf\u5c0f\u5b69\u8b80\u7269\u7684\u53ef\u8b80 \u6027[6]\u3002\u53ef\u8b80\u6027\u7814\u7a76\u4e00\u76f4\u6301\u7e8c\u4e0d\u65b7\u7684\u767c\u5c55\uff0c\u64da Chall \u8207 Dale \u5728 1995 \u5e74\u7684\u7d71\u8a08\uff0c\u5230 1980 \u5e74\u70ba\u6b62\u76f8\u95dc\u7684\u53ef\u8b80\u6027\u516c\u5f0f\u5df2\u7d93\u8d85\u904e 200 \u591a\u5247\u6587\u4ef6\u53ef\u8b80\u6027\u516c\u5f0f[7]\u3002\u9019\u4e9b\u50b3\u7d71\u7684\u53ef\u8b80\u6027\u516c \u5f0f\u5927\u591a\u90fd\u662f\u4f7f\u7528\u8a9e\u8a00\u7279\u5fb5\u4f86\u8a55\u91cf\u6587\u4ef6\u7684\u53ef\u8b80\u6027\uff0c\u4f8b\u5982\uff1a\u8457\u540d\u7684 Flesch Reading Ease \u516c\u5f0f \u4ee5\u8a5e\u5f59\u97f3\u7bc0\u6578\u505a\u70ba\u8a9e\u610f\u7684\u6307\u6a19\uff0c\u4ee5\u53e5\u5b50\u7684\u9577\u5ea6\u4f5c\u70ba\u8a9e\u6cd5\u7684\u6307\u6a19\uff0c\u8a08\u7b97\u8a5e\u5f59\u7684\u5e73\u5747\u97f3\u7bc0\u6578 \u8207\u6587\u4ef6\u7684\u5e73\u5747\u53e5\u5b50\u9577\u5ea6\u4f86\u8a55\u4f30\u6587\u4ef6\u96e3\u5ea6\uff0c\u7576\u6587\u4ef6\u7684\u8a5e\u5f59\u97f3\u7bc0\u6578\u6108\u591a\u3001\u53e5\u5b50\u6108\u9577\uff0c\u5247\u8a72\u6587 \u4ef6\u6108\u56f0\u96e3[8]\u3002Chall \u548c Dale(1995)\u52a0\u5165\u4e86\u300c\u96e3\u8a5e\u6bd4\u7387\u300d\u505a\u70ba\u8a55\u4f30\u6587\u4ef6\u96e3\u5ea6\u7684\u65b9\u5f0f\uff0c\u96e3\u8a5e \u51fa\u73fe\u6108\u591a\uff0c\u8868\u793a\u6587\u4ef6\u6108\u56f0\u96e3[7]\u3002\u81f3\u4eca\uff0c\u53ef\u8b80\u6027\u6a21\u578b\u7684\u767c\u5c55\u4f9d\u820a\u84ec\u52c3\u767c\u5c55\uff0c\u4e26\u96a8\u8457\u6a5f\u5668 \u5b78\u7fd2\u6f14\u7b97\u6cd5\u7684\u5d1b\u8d77\uff0c\u7814\u7a76\u4eba\u54e1\u5f97\u4ee5\u7528\u66f4\u7d30\u7dfb\u7684\u6f14\u7b97\u6cd5\u8b93\u53ef\u8b80\u6027\u6a21\u578b\u53ef\u4ee5\u7d0d\u5165\u66f4\u591a\u5143\u7684\u53ef \u8b80\u6027\u6307\u6a19\uff0c\u4ee5\u63d0\u5347\u6a21\u578b\u6e96\u78ba\u7387" |
| }, |
| "TABREF2": { |
| "content": "<table><tr><td>(\u4e09)\u3001\u8a13\u7df4\u53ef\u8b80\u6027\u6a21\u578b \u56db\u3001\u5be6\u9a57\u7d50\u679c</td><td>INPUT</td><td>PROJECTION</td><td>OUTPUT</td></tr><tr><td colspan=\"4\">W(t-2) \u5efa\u7f6e\u8de8\u9818\u57df\u6587\u4ef6\u7684\u53ef\u8b80\u6027\u6a21\u578b\u6d41\u7a0b\u5982\u5716 3 \u6240\u793a\uff0c\u672c\u7814\u7a76\u6750\u6599\u9078\u81ea 98 \u5e74\u5ea6\u81fa\u7063 H\u3001K\u3001N \u672c\u7814\u7a76\u7684\u5be6\u9a57\u7d50\u679c\u5982\u8868\u4e00\u548c\u8868\u4e8c\u6240\u793a\uff0c\u800c \u56db\u7a2e\u53ef\u8b80\u6027\u6a21\u578b\u7684\u932f\u8aa4\u77e9\u9663\u5206\u5225\u5982\u8868\u4e09\u3001\u8868\u56db\u3001</td></tr><tr><td colspan=\"4\">\u4e09\u5927\u51fa\u7248\u793e\u6240\u51fa\u7248\u7684 1-12 \u5e74\u7d1a\u5be9\u5b9a\u7248\u7684\u570b\u8a9e\u79d1\u3001\u793e\u6703\u79d1\u3001\u81ea\u7136\u79d1\u53ca\u9ad4\u80b2\u548c\u5065\u5eb7\u6559\u80b2\u7b49 \u8868\u4e94\u53ca\u8868\u516d\u3002\u5f9e\u7d50\u679c\u53ef\u4ee5\u767c\u73fe\u4e0d\u8ad6\u662f\u5728\u4e09\u7a2e\u9818\u57df\u6587\u672c\u9084\u662f\u56db\u7a2e\u9818\u57df\u6587\u672c\u7684\u60c5\u6cc1\u4e0b\uff0c\u6df1\u5c64</td></tr><tr><td colspan=\"4\">\u7684\u6587\u672c\u503c\u5f97\u5546\u69b7\u3002Kanungo \u548c Orr(2009)\u5247\u662f\u91dd\u5c0d\u641c\u5c0b\u5f15\u64ce\u6240\u641c\u5c0b\u51fa\u4f86\u7684\u7db2\u9801\u6458\u8981\u4f86\u8a55 W(t-1) \u56db\u500b\u9818\u57df\u7684\u6559\u79d1\u66f8\u5168\u90e8\u5171\u8a08 6,230 \u7bc7\uff0c\u5404\u7248\u672c\u6559\u79d1\u66f8\u5747\u7d93\u7531\u5c08\u5bb6\u6839\u64da\u8ab2\u7a0b\u7db1\u8981\u7de8\u5236\u800c\u6210\u3002 \u985e\u795e\u7d93\u7db2\u8def\u7684\u6e96\u78ba\u7387\u90fd\u512a\u65bc\u652f\u5411\u91cf\u6a5f\u3002\u7136\u800c\u6211\u5011\u4e5f\u4e0d\u96e3\u767c\u73fe\u5728\u52a0\u5165 1,582 \u7bc7\u7684\u9ad4\u80b2\u548c\u5065</td></tr><tr><td colspan=\"4\">\u91cf\u53ef\u8b80\u6027\uff0c\u53ef\u60dc\u6240\u63a1\u7528\u7684\u53ef\u8b80\u6027\u7279\u5fb5\u4ecd\u820a\u70ba\u4e00\u822c\u7684\u8a9e\u8a00\u7279\u5fb5\uff0c\u4e26\u7121\u6cd5\u8868\u5fb5\u7279\u5b9a\u9818\u57df\u6587\u4ef6 \u7684\u77e5\u8b58\u7d50\u69cb\uff0c\u56e0\u6b64\u5176\u6587\u4ef6\u53ef\u8b80\u6027\u7d50\u679c\u662f\u5426\u80fd\u9032\u4e00\u6b65\u5c0d\u61c9\u7db2\u9801\u9069\u8b80\u7684\u5e74\u9f61\u5247\u9700\u9032\u4e00\u6b65\u7684\u9a57 Negative Sampling \u5169\u7a2e\u6a21\u5f0f\u4f86\u589e\u9032\u8a13\u7df4\u7684\u6548\u80fd\u3002\u7136\u800c\uff0c\u4e0d\u8ad6\u662f\u9023\u7e8c\u8a5e\u888b\u6a21\u578b\u9084\u662f\u7565\u8a5e\u6a21 \u578b\u90fd\u662f\u57fa\u65bc\u4e00\u500b\u9577\u5ea6\u4f86\u770b\u8a5e\u5f59\u4e4b\u9593\u7684\u95dc\u4fc2\uff0c\u5373\u6240\u8b02\u7684 Shallow Window-Based \u7684\u65b9\u6cd5\u3002 SUM W(t) \u672c\u7814\u7a76\u5be6\u9a57\u62c6\u6210\u5169\u500b\u8cc7\u6599\u96c6\u5206\u5225\u70ba\uff1a\u4e00\u3001\u8cc7\u6599\u96c6 A\uff1a\u7531\u570b\u8a9e\u79d1\u3001\u793e\u6703\u79d1\u53ca\u81ea\u7136\u79d1\u7b49\u4e09\u500b \u5eb7\u6559\u80b2\u5f8c\uff0c\u6a21\u578b\u5206\u985e\u7684\u96e3\u5ea6\u5927\u5e45\u5ea6\u7684\u4e0a\u5347\u3002\u5c0d\u652f\u5411\u91cf\u6a5f\u6a21\u578b\u800c\u8a00\uff0c\u6e96\u78ba\u7387\u6e1b\u5c11\u4e86 9.5% \u9818\u57df\u7684\u6559\u79d1\u66f8\u5171\u8a08 4,648 \u7bc7\u3002\u4e8c\u3001\u8cc7\u6599\u96c6 B\uff1a\u7531\u570b\u8a9e\u79d1\u3001\u793e\u6703\u79d1\u3001\u81ea\u7136\u79d1\u53ca\u9ad4\u80b2\u548c\u5065\u5eb7 \u6559\u80b2\u7b49\u56db\u500b\u9818\u57df\u7684\u6559\u79d1\u66f8\u5171\u8a08 6,230 \u7bc7\u3002\u85c9\u6b64\u89c0\u5bdf\u5728\u8cc7\u6599\u96c6\u6108\u8907\u96dc\u7684\u60c5\u6cc1\u4e0b\uff0c\u5c0d\u65bc\u652f\u5411 \u7684\u6e96\u78ba\u7387\uff0c\u800c\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u53ea\u6709\u6e1b\u5c11\u4e86 7.32%\u7684\u6e96\u78ba\u7387\u3002\u9019\u986f\u793a\u5728\u6587\u672c\u53ef\u8b80\u6027\u5206\u985e\u7684</td></tr><tr><td colspan=\"4\">\u8b49[30]\u3002 Jeffrey Pennington \u5247\u662f\u5728 2014 \u5e74\u63d0\u51fa\u4e00\u500b GloVe \u7684\u6f14\u7b97\u6cd5\u4f86\u540c\u6642\u8003\u616e\u5168\u57df\u53ca\u5340\u57df\u8a5e\u5f59 \u91cf\u6a5f\u53ca\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u6240\u9020\u6210\u7684\u5f71\u97ff\u70ba\u4f55\u3002\u800c \u6574\u5be6\u9a57\u7684\u6d41\u7a0b\u7686\u63a1\u7528 5-fold \u4ea4\u4e92\u9a57\u8b49\u7684\u65b9 \u9019\u500b\u7814\u7a76\u9818\u57df\u4e2d\uff0c\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u6bd4\u652f\u5411\u91cf\u6a5f\u66f4\u80fd\u5920\u8655\u7406\u66f4\u70ba\u8907\u96dc\u7684\u8cc7\u6599\u3002</td></tr><tr><td colspan=\"4\">\u4e4b\u9593\u7684\u95dc\u4fc2\uff0c\u4ee5\u63d0\u5347 Word Embedding \u7684\u6548\u679c[39]\u3002\u800c \u6839\u64da\u904e\u53bb\u7684\u5be6\u9a57\uff0c\u9023\u7e8c\u8a5e\u888b\u6a21\u578b\u3001 W(t+1) \u5f0f\u9032\u884c\uff0c\u9996\u5148\u5c07\u6587\u4ef6\u5229\u7528 WECAn[43]\u4f86\u9032\u884c\u4e2d\u6587\u6587\u4ef6\u7684\u65b7\u8a5e\uff0c\u518d\u5c07\u8a13\u7df4\u8cc7\u6599\u5229\u7528 \u9664\u4e86\u53ef\u8b80\u6027\u6307\u6a19\u7684\u554f\u984c\u4e4b\u5916\uff0c\u53d7 \u76ca\u65bc\u81ea\u7136\u8a9e\u8a00\u8655\u7406\u6280\u8853\u8207\u6a5f\u68b0\u5b78\u7fd2\u6f14\u7b97\u6cd5\u7684\u5d1b\u8d77\uff0c \u7814\u7a76\u4eba\u54e1\u5f97\u4ee5\u7528\u66f4\u7cbe\u7dfb\u7684\u6a21\u578b\u6f14\u7b97\u6cd5\u4f86\u6e2c\u91cf\u6587\u672c\u7684\u53ef\u8b80\u6027\uff0c\u4f7f\u53ef\u8b80\u6027\u6a21\u578b\u4e0d\u50c5\u53ef\u4ee5\u7d0d\u5165 \u66f4\u591a\u5143\u7684\u53ef\u8b80\u6027\u6307\u6a19\uff0c\u4e26\u4e14\u5c0d\u65bc\u6a21\u578b\u7684\u6548\u80fd\u4ea6\u6709\u660e\u986f\u7684\u63d0\u5347[31],[32],[34] \uff0c\u800c \u5176\u4e2d\u6240\u63a1 \u7565\u8a5e\u6a21\u578b\u53ca GloVe \u5728\u53ef\u8b80\u6027\u7814\u7a76\u7684\u6548\u80fd\u5dee\u7570\u4e0d\u5927\u7684\u60c5\u6cc1\u4e0b\uff0c\u672c\u8ad6\u6587\u5c07\u57fa\u65bc\u9023\u7e8c\u8a5e\u888b\u6a21\u578b Word2Vec[38]\u4f86\u5206\u5225\u5f97\u5230\u9023\u7e8c\u8a5e\u888b\u6a21\u578b\u8a5e\u5411\u91cf\u5c0d\u7167\u8868\u3002\u63a5\u8457\u5c07\u8a13\u7df4\u8cc7\u6599\u7684\u6bcf\u4e00\u7bc7\u8ab2\u6587\u4f9d \u8868\u4e00\u3001\u5be6\u9a57\u4e00\uff1a\u9023\u7e8c\u8a5e\u888b\u6a21\u578b 100 \u7dad\u5ea6\u4e4b\u4e09\u7a2e\u9818\u57df\u6587\u672c\u6548\u80fd\u6bd4\u8f03 \u64da\u4f7f\u7528\u5230\u7684\u8a5e\u5f59\u5f9e\u8a5e\u5411\u91cf\u5c0d\u7167\u8868\u4e2d\u53d6\u51fa\u5411\u91cf\uff0c\u4e26\u5c07\u9019\u4e9b\u5411\u91cf\u5168\u90e8\u76f8\u52a0\uff0c\u6700\u5f8c\u6240\u5f97\u5230\u7684\u5411 \u8a5e\u5411\u91cf\u8868\u793a\u65b9\u5f0f\u4f86\u642d\u914d\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u5efa\u69cb\u51fa\u4e00\u500b\u8de8\u9818\u57df\u6587\u4ef6\u7684\u53ef\u8b80\u6027\u6a21\u578b[40]\u3002 W(t+2) \u91cf\u4fbf\u662f\u9019\u4e00\u7bc7\u8ab2\u6587\u7684\u53ef\u8b80\u6027\u7279\u5fb5\uff0c\u800c\u5b83\u7684\u985e\u5225\u5c31\u662f\u8ab2\u6587\u6240\u5c6c\u7684\u5e74\u7d1a\u3002\u672c\u7814\u7a76\u5206\u5225\u5229\u7528 \u9069\u7528\u5e74\u7d1a \u9069\u7528\u9818\u57df \u5206\u985e\u6f14\u7b97\u6cd5 \u6e96\u78ba\u7387(%)</td></tr><tr><td colspan=\"4\">\u7528\u5206\u985e\u7684\u5de5\u5177\u53c8\u4ee5\u652f\u5411\u91cf\u6a5f(Support Vector Machine, SVM)\u6700\u70ba\u5e38\u898b\u3002\u7136\u800c\u652f\u5411\u91cf\u6a5f\u76f8\u5c0d \u65bc\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def(Deep Neural Network, DNN)\u800c\u8a00\uff0c\u662f\u5c6c\u65bc\u4e00\u7a2e\u6dfa\u5c64\u7684\u7d50\u69cb\uff0c\u76ee\u524d\u5df2 \u6709\u7814\u7a76\u8b49\u660e\u9019\u7a2e\u6dfa\u5c64\u7d50\u69cb\u7684\u6a5f\u68b0\u5b78\u7fd2\u6f14\u7b97\u6cd5\u5728\u89e3\u6c7a\u7c21\u55ae\u6216\u9650\u5236\u8f03\u591a\u7684\u5206\u985e\u554f\u984c\u4e0a\uff0c\u662f\u53ef INPUT PROJECTION OUTPUT W(t-2) \u5716\u4e8c\u3001\u7565\u8a5e\u6a21\u578b\u8a13\u7df4\u6f14\u7b97\u6cd5 \u8cc7\u6599\u7684\u53ef\u8b80\u6027\u7279\u5fb5\u5f8c\uff0c\u4fbf\u53ef\u8f38\u5165\u81f3\u5df2\u8a13\u7df4\u597d\u7684\u53ef\u8b80\u6027\u6a21\u578b\u4f86\u9810\u6e2c\u6587\u4ef6\u7684\u5e74\u7d1a\u503c\u3002 (\u4e8c)\u3001\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def Keras [44] \u548c LIBSVM[45]\u4f86\u8a13\u7df4\u51fa\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u53ca\u652f\u5411\u91cf\u6a5f\u53ef\u8b80\u6027\u6a21\u578b\u3002\u5728\u9a57\u8b49\u53ef \u8b80\u6027\u6a21\u578b\u7684\u968e\u6bb5\uff0c\u672c\u7814\u7a76\u5c07\u6e2c\u8a66\u8cc7\u6599\u4f7f\u7528\u5230\u7684\u8a5e\u5f59\u4e00\u6a23\u5f9e\u8a5e\u5411\u91cf\u5c0d\u7167\u8868\u53d6\u51fa\u5411\u91cf\uff0c\u4e26\u5c07 \u9019\u4e9b\u5411\u91cf\u5168\u90e8\u76f8\u52a0\uff0c\u5982\u9047\u5230\u8a5e\u5411\u91cf\u5c0d\u7167\u8868\u6c92\u6709\u7684\u8a5e\u5f59\u6642\uff0c\u5247\u4e0d\u8655\u7406\u8a72\u8a5e\u5f59\u3002\u5728\u53d6\u5f97\u6e2c\u8a66 1-12 \u5e74\u7d1a \u570b\u8a9e\u3001\u793e\u6703\u3001\u81ea\u7136\u5171\u8a08 \u652f\u5411\u91cf\u6a5f 70.83 4,648 \u7bc7 \u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def 74.27</td></tr><tr><td colspan=\"4\">\u4ee5\u5f97\u5230\u4e0d\u932f\u7684\u6548\u679c\u3002\u4f46\u662f\u53d7\u9650\u65bc\u6a21\u578b\u5efa\u6a21\u548c\u8868\u793a\u7684\u80fd\u529b\uff0c\u7576\u8655\u7406\u7684\u554f\u984c\u662f\u66f4\u70ba\u8907\u96dc\u7684\u60c5 \u8868\u4e8c\u3001\u5be6\u9a57\u4e8c\uff1a\u9023\u7e8c\u8a5e\u888b\u6a21\u578b 100 \u7dad\u5ea6\u4e4b\u56db\u7a2e\u9818\u57df\u6587\u672c\u6548\u80fd\u6bd4\u8f03 W(t-1) SUM \u8cc7\u6599\u96c6A(4648\u7bc7) \u8cc7\u6599\u96c6B(6230\u7bc7) \u9069\u7528\u5e74\u7d1a \u9069\u7528\u9818\u57df \u5206\u985e\u6f14\u7b97\u6cd5 \u6e96\u78ba\u7387(%) \u5f62\u4e0b\uff0c\u5c31\u6703\u9762\u81e8\u5404\u7a2e\u7684\u56f0\u96e3[35]\u3002\u56e0\u6b64\uff0c\u5f9e\u4e0a\u8ff0\u7684\u7814\u7a76\u53ef\u4ee5\u767c\u73fe\uff0c\u5c07\u53ef\u8b80\u6027\u6a21\u578b\u904b\u7528\u81f3 \u7db2\u8def\u6587\u4ef6\u662f\u4e00\u500b\u5fc5\u7136\u7684\u8da8\u52e2\uff0c\u4f46\u4e5f\u56e0\u70ba\u7db2\u8def\u6587\u4ef6\u6709\u8457\u8a31\u591a\u8907\u96dc\u4e14\u7121\u6cd5\u638c\u63a7\u7684\u56e0\u7d20\uff0c\u81f4\u4f7f \u53ef\u8b80\u6027\u6a21\u578b\u7684\u767c\u5c55\u9700\u8981\u8003\u616e\u7684\u66f4\u52a0\u5468\u5ef6\u3002\u56e0\u6b64\uff0c\u672c\u8ad6\u6587\u5c07\u5229\u7528\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u53ca\u8a5e\u5411\u91cf W(t) \u65b7\u8a5e 1-12 \u5e74\u7d1a \u570b\u8a9e\u3001\u793e\u6703\u3001\u81ea\u7136\u3001 \u652f\u5411\u91cf\u6a5f 61.33 \u9ad4\u80b2\u548c\u5065\u5eb7\u6559\u80b2\u5171\u8a08 6,230 \u7bc7 \u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def 66.95</td></tr><tr><td colspan=\"2\">\u6280\u8853\u4f86\u5efa\u69cb\u8de8\u9818\u57df\u6587\u4ef6\u7684\u53ef\u8b80\u6027\u6a21\u578b\u3002 W(t+1)</td><td/><td/></tr><tr><td/><td>\u8a13\u7df4\u8cc7\u6599</td><td>\u6e2c\u8a66\u8cc7\u6599</td><td/></tr><tr><td colspan=\"4\">W(t+2) \u4e09\u3001\u57fa\u65bc\u6df1\u5c64\u985e\u795e\u7d93\u7db2\u8def\u53ca\u8a5e\u5411\u91cf\u8868\u793a\u6cd5\u4e4b\u53ef\u8b80\u6027\u6a21\u578b\u5efa\u7acb Word Embedding</td></tr><tr><td/><td colspan=\"3\">\u5716\u4e00\u3001\u9023\u7e8c\u8a5e\u888b\u6a21\u578b\u8a13\u7df4\u6f14\u7b97\u6cd5</td></tr><tr><td colspan=\"3\">(column vectors)\uff0c\u5206\u5225\u5c0d\u61c9\u5404\u5e74\u7d1a\uff0c\u5982\u4e0b\u5f0f(1)\uff1a (\u4e00)\u3001\u8a5e\u5411\u91cf\u8868\u793a \u8a5e\u5411\u91cf\u5c0d\u7167\u8868</td><td/></tr><tr><td colspan=\"4\">= | 1 2 \u2026 12 | \u672c\u8ad6\u6587\u63d0\u51fa\u7684\u65b9\u6cd5\u70ba\u9650\u5236\u9130\u8fd1\u5e74\u7d1a\u7684\u884c\u9805\u91cf\u8ddd\u96e2\uff0c\u76f8\u9130\u7684\u5e74\u7d1a\u61c9\u8a72\u6709\u76f8\u8fd1\u7684\u5411\u91cf\uff0c \u6839\u64da\u8cc7\u6599\u52a0\u7e3d (1) 5-fold cross \u8a5e\u5411\u91cf 25]\uff0c\u56e0\u6b64\u5982\u4f55\u624d\u6539\u5584\u53ef\u8b80\u6027\u6a21\u578b\u4f86\u9069\u7528\u65bc\u5728\u7db2\u9801\u6587\u672c\u4fbf\u662f\u503c\u5f97\u7814\u7a76\u7684\u8b70\u984c\u3002 validation \u53ef\u4ee5\u81ea\u7136\u5730\u8868\u9054\u5e74\u7d1a\u7684\u9023\u7e8c\u6027\u3002\u6b64\u6b63\u5247\u9805\u53ef\u4ee5\u8868\u9054\u70ba\u4e0b\u5f0f(2)\uff1a SVM / DNN</td></tr><tr><td colspan=\"4\">Miltsakaki \u5728 2007 \u5e74\u63d0\u51fa Read-X \u7cfb\u7d71\u4f86\u91dd\u5c0d\u4e0d\u540c\u985e\u5225\u7db2\u9801\u6587\u672c\u9032\u884c\u53ef\u8b80\u6027\u7684\u8a55\u4f30\uff0c\u5b83 \u662f\u5229\u7528\u4e09\u7a2e\u53ef\u8b80\u6027\u516c\u5f0f\uff1aLix readability formula\u3001 Rix readability formula \u548c Coleman-Liau ( ) = \u2211 \u2016 \u2212 +1 \u2016 11 =1 (2) SVM \u6a21\u578b / \u6211\u5011\u5e0c\u671b\u6b64\u6b63\u5247\u9805\u53ef\u4ee5\u9650\u5236\u9130\u8fd1\u5e74\u7d1a\u5411\u91cf\u7684\u8ddd\u96e2\uff0c\u800c\u5b8c\u6574\u7684\u6e1b\u640d\u51fd\u6578\u70ba\u4ea4\u53c9\u71b5(cross DNN \u6a21\u578b</td></tr><tr><td colspan=\"4\">redability formula \u7b49\u4f86\u8a55\u91cf\u6587\u4ef6\u7684\u53ef\u8b80\u6027\u96e3\u5ea6\uff0c\u4f46 Read-X \u7cfb\u7d71\u672a\u5c07\u4e09\u7a2e\u53ef\u8b80\u6027\u7684\u96e3\u5ea6\u9032 entropy)\u548c\u6b63\u5247\u9805\u7684\u7d50\u5408\uff0c\u5982\u4e0b\u5f0f(3)\uff1a ( ) = \u2212 \u2211 ( \u2212 log ) 12 =1 \u2212 \u2211 \u2016 \u2212 +1 \u2016 11 =1 \u6587\u672c\u53ef\u8b80\u6027 (3) \u9810\u6e2c\u7d50\u679c</td></tr><tr><td colspan=\"4\">\u5176\u4e2d \u70ba\u5e74\u7d1a\u6a19\u8a18\uff0c \u70ba\u6a21\u578b\u8f38\u51fa\u5e74\u7d1a i \u7684\u6a5f\u7387\u3002\u6211\u5011\u85c9\u6b64\u9f13\u52f5\u8f38\u51fa\u5c64\u53c3\u6578\u5448\u73fe 12</td></tr><tr><td colspan=\"4\">\u5e74\u7d1a\u7684\u6d41\u5f62(manifold)\uff0c\u5373\u76f8\u9130\u5169\u500b\u5e74\u7d1a\u5f7c\u6b64\u5728\u8f38\u51fa\u5c64\u7a7a\u9593\u4e2d\u76f8\u8fd1\u3002 \u5716\u4e09\u3001\u53ef\u8b80\u6027\u6a21\u578b\u8a13\u7df4\u53ca\u6e2c\u8a66\u6d41\u7a0b\u5716</td></tr></table>", |
| "num": null, |
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| "text": "Coleman-Liau Readability Formula \u7684\u96e3\u5ea6\u9032\u884c\u6574\u5408\uff0c\u7136\u800c\u537b\u4e5f\u767c\u73fe\u9019\u6a23\u5b50\u7684\u6574\u5408\u65b9\u5f0f\u7121\u6cd5\u6709\u6548\u5340\u5206\u51fa 9-10 \u5e74\u7d1a\u53ca 11-13 \u5e74\u7d1a\u7684\u96e3\u5ea6[28]\u3002Eickhoff \u7b49\u4eba\u5247\u662f\u85c9\u7531\u5075\u6e2c\u4e3b\u984c\u7684\u65b9\u5f0f\u4f86\u5340\u5206\u54ea\u7a2e\u7db2\u9801\u9069\u5408\u5c0f\u5b69 \u5b50\u95b1\u8b80[29]\u3002\u7136\u800c\u6b64\u7a2e\u5224\u5b9a\u6587\u4ef6\u53ef\u8b80\u6027\u7684\u65b9\u5f0f\u662f\u5426\u9069\u7528\u65bc\u87ba\u65cb\u5f0f\u6559\u5b78(Spiral Curriculum) \u8a5e\u5411\u91cf\u8868\u793a\u7684\u89c0\u5ff5\u6700\u65e9\u7531 Hinton \u5728 1986 \u5e74\u6240\u63d0\u51fa\uff0c\u53c8\u88ab\u7a31\u70ba\u8a5e\u8868\u793a(Word Representation or Word Embedding)[36] \u3002 Bengio \u5728 2003 \u5e74\u63d0\u51fa\u56de\u994b\u5f0f\u985e\u795e\u7d93\u7db2\u8def\u8a9e\u8a00\u6a21\u578b (Feed-forward Neural Network Language Model(FFNNLM)\u7684\u8a13\u7df4\u67b6\u69cb\uff0c\u5f9e\u6587\u4ef6\u4e2d\u8a5e\u5f59\u524d \u5f8c\u76f8\u9130\u7684\u95dc\u4fc2\u4f86\u6c42\u53d6\u8a5e\u5411\u91cf\u8868\u793a[37]\u3002\u800c\u8fd1\u671f Google \u6240\u767c\u8868\u7684 Word2Vec \u5247\u53ef\u8996\u70ba FFNNLM \u7684\u5f8c\u7e7c\u65b9\u6cd5[38] \u3002\u7136\u800c\u8ddf FFNNLM \u67b6\u69cb\u4e0d\u4e00\u6a23\u7684\u662f\uff0cWord2vec \u53bb\u9664\u4e86 FFNNLM \u5728\u8a13\u7df4\u6642\u6700\u8017\u6642\u7684\u975e\u7dda\u6027\u96b1\u85cf\u5c64\uff0c\u50c5\u4fdd\u7559\u8f38\u5165\u5c64\u3001\u6295\u5f71\u5c64\u548c\u8f38\u51fa\u5c64\uff0c\u4f7f\u5176\u67b6\u69cb\u66f4\u52a0\u7c21\u55ae\u3002 Word2vec \u63d0\u4f9b\u4e86\u4e8c\u7a2e\u8a13\u7df4\u65b9\u5f0f\uff0c\u5206\u5225\u662f\u9023\u7e8c\u8a5e\u888b\u6a21\u578b(Continuous Bag-of-words Model, CBOW)\u53ca\u7565\u8a5e\u6a21\u578b(Skip-gram Model, Skip-gram)\u3002\u9023\u7e8c\u8a5e\u888b\u6a21\u578b\u4e3b\u8981\u7684\u7cbe\u795e\u662f\u7531\u76ee\u6a19\u8a5e \u4e4b\u5916\u7684\u524d\u5f8c\u6587\u4f86\u9810\u6e2c\u76ee\u6a19\u8a5e\u7684\u6a5f\u7387\uff1b\u800c\u7565\u8a5e\u6a21\u578b\u7684\u8a13\u7df4\u65b9\u5f0f\u6b63\u597d\u76f8\u53cd\uff0c\u5b83\u662f\u7531\u76ee\u6a19\u8a5e\u672c \u8eab\u4f86\u53bb\u9810\u6e2c\u524d\u5f8c\u6587\u7684\u6a5f\u7387\uff0c\u4e8c\u7a2e\u8a13\u7df4\u6a21\u578b\u793a\u610f\u5716\u5982\u5716 1 \u548c\u5716 2 \u6240\u793a\u3002\u5728 Word2Vec \u4e2d\u4e0d \u8ad6\u662f\u9023\u7e8c\u8a5e\u888b\u6a21\u578b\u9084\u662f\u7565\u8a5e\u6a21\u578b\uff0c\u5728\u8f38\u51fa\u5c64\u90fd\u53ef\u4ee5\u63a1\u7528 Hierarchical Softmax \u6216\u662f" |
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