ACL-OCL / Base_JSON /prefixO /json /O01 /O01-1012.json
Benjamin Aw
Add updated pkl file v3
6fa4bc9
{
"paper_id": "O01-1012",
"header": {
"generated_with": "S2ORC 1.0.0",
"date_generated": "2023-01-19T08:09:37.077851Z"
},
"title": "Automatic Classification of Chinese Unknown Verbs",
"authors": [],
"year": "",
"venue": null,
"identifiers": {},
"abstract": "We present a new method for automatic classification of Chinese unknown verbs. The method employs the instance-based categorization using the k-nearest neighbor method for the classification. The accuracy of the classifier is about 70.92%.",
"pdf_parse": {
"paper_id": "O01-1012",
"_pdf_hash": "",
"abstract": [
{
"text": "We present a new method for automatic classification of Chinese unknown verbs. The method employs the instance-based categorization using the k-nearest neighbor method for the classification. The accuracy of the classifier is about 70.92%.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Abstract",
"sec_num": null
}
],
"body_text": [
{
"text": "y,1 x,1 y,1 x,1 y,1 x,1 \u2229 \u2212 = \u2229 = \u2229 \u800c\u7b2c\u3193\u90e8\u5206\u7684\u76f8\u4f3c\u5ea6\u7684\u5b9a\u7fa9\u70ba\uff1a ( )( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) \uf8f7 \uf8f7 \uf8f8 \uf8f6 \uf8ec \uf8ec \uf8ed \uf8eb \u2212 \uf8f7 \uf8f7 \uf8f8 \uf8f6 \uf8ec \uf8ec \uf8ed \uf8eb \u2229 \u2212 = \uf8f7 \uf8f7 \uf8f8 \uf8f6 \uf8ec \uf8ec \uf8ed \uf8eb \uf8f7 \uf8f7 \uf8f8 \uf8f6 \uf8ec \uf8ec \uf8ed \uf8eb \u2212 \u2229 = \u2211 \u2211 = = = = 1 n / System /Entropy sem Sem Entropy System Entropy 1 n / System /Entropy Sem Sem nContent Informatio ...Sem Sem , ...Sem Sem core SecondaryS n 2 i j y, i x, {1...m} j j y, i x, n 2 i {1...m} j m y, y,2 n x, x,2 Max Max \u6211\u5011\u4ee4(n>=m)\uff0c\u4e5f\u5c31\u662f\u7b2c\u3192\u500b\u8a5e\u689d\u7684\u5b9a\u7fa9\u7684\u7fa9\u539f\u591a\u65bc\u6216\u7b49\u65bc\u7b2c\u3193\u500b\u8a5e\u689d\u7684\u7fa9 \u539f\uff0c\u5f9e\u7b2c\u3192\u500b\u8a5e\u689d\u3197\u7b2c\u3193\u500b\u7fa9\u539f\u958b\u59cb\uff0c\u6bcf\u500b\u7fa9\u539f\u8207\u7b2c\u3193\u500b\u8a5e\u689d\u3197\u7684\u6bcf\u500b\u7fa9\u539f\u8a08\u7b97 \u76f8\u4f3c\u5ea6\uff0c\u7b2c\u3192\u500b\u8a5e\u689d\u3197\u6bcf\u500b\u7fa9\u539f\u7559\u3198\u8207\u7b2c\u3193\u500b\u8a5e\u689d\u7fa9\u539f\u76f8\u4f3c\u5206\u6578\u6700\u9ad8\u7684\u7d44\u5408\uff0c\u5c07 \u7b2c\u3192\u500b\u8a5e\u689d\u3197\u6bcf\u500b\u7fa9\u539f\u5f97\u5230\u7684\u5206\u6578\u5e73\u5747\uff0c\u5c31\u662f\u6211\u5011\u6240\u5b9a\u7fa9\u7684\u7b2c\u3193\u90e8\u5206\u7684\u76f8\u4f3c\u5ea6\u3002 \u4ee5\u3196\u5169\u5f0f\u3197\u5404\u9805\u7686\u9664\u4ee5 Entropy \u662f\u70ba\u7dad\u6301\u76f8\u4f3c\u503c\u4ecb\u65bc 0,1 \u4e4b\u9593\u3002 (System) 2-2-2 \u8a5e\u985e\u76f8\u4f3c\u5ea6\u6e2c\u91cf \u6211\u5011\u5c07 1.0 \u7248\u3197\u7684\u53e5\u7d50\u69cb\u6a39\u3197\u6b78\u7d0d\u51fa\u898f\u5247\uff0c\u4e26\u7d71\u8a08\u6bcf\u689d\u898f\u5247\u51fa\u73fe\u7684\u983b\u7387\uff0c\u5982 \u5716 1",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "3-1 \u8a9e\u610f\u6bd4\u91cd\u76f8\u4f3c\u5ea6\u8a55\u91cf \u6211\u5011\u9996\u5148\u8981\u56fa\u5b9a\u5169\u500b\u8b8a\u6578\uff0c\u8a9e\u610f\u8207\u8a5e\u985e\u7684\u6bd4\u91cd\u8207 K \u503c\uff0c\u624d\u80fd\u89c0\u5bdf\u51fa\u76f8\u4f3c\u5ea6\u6bd4 \u91cd\u7684\u8b8a\u5316\u5c0d\u6b63\u78ba\u7387\u7684\u5f71\u97ff\u3002\u56e0\u6b64\u5148\u7d66\u4e88 K=1\uff0c\u8a9e\u610f\u8207\u8a5e\u985e\u6bd4\u91cd\u70ba 1 \u8207 0\uff0c\u4f9d\u7167\u76f8 \u4f3c\u5ea6\u6bd4\u91cd\u7684\u8b8a\u5316\u5c0d\u6b63\u78ba\u7387\u7684\u5f71\u97ff\u88fd\u6210\u3198\u8868\u3002 \u8868\u683c 2 \u76f8\u4f3c\u5ea6\u6bd4\u91cd\u8207\u6b63\u78ba\u7387\u8b8a\u5316\u8868 \u8a9e\u610f\u8207\u8a5e\u985e\u6bd4\u91cd(\u8a9e\u610f,\u8a5e\u985e) \u8a9e\u610f\u76f8\u4f3c\u5ea6\u6bd4\u91cd(w 1 ,w 2 ) \u6b63\u78ba\u7387 (1,0) (1,0) 54.04%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "(1,0) (0.9,0.1) 57.58% (1,0) (0.8,0.2) 57.70%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "(1,0) (0.7,0.3) 57.58%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "(1,0) (0.6,0.4) 56.97%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "(1,0) (0.5,0.5) 56.85%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "(1,0) (0.4,0.6) 56.23%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "(1,0) (0.3,0.7) 55.87%",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "( ",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "",
"sec_num": null
},
{
"text": "EQUATION",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [
{
"start": 0,
"end": 8,
"text": "EQUATION",
"ref_id": "EQREF",
"raw_str": "1,0) (0.2,0.8) 56.11% (1,0) (0.1,0.9) 56.11% (1,0) (0,1) 56.09% \u7531\u3196\u8868\u3197\u53ef\u770b\u51fa\u4e3b\u8981\u7fa9\u539f\u7684\u6bd4\u91cd\u70ba 0.8 \u8207\u6b21\u8981\u7fa9\u539f\u7684\u6bd4\u91cd\u70ba 0.2 \u6642\u53ef\u4ee5\u5f97\u5230\u6700\u9ad8 \u7684\u6b63\u78ba\u7387\uff0c\u56e0\u6b64\u5728\u672c\u5be6\u9a57\u3197\u6211\u5011\u4f7f\u7528 0.8 \u8207 0.2 \u4f5c\u70ba\u4e3b\u8981\u7fa9\u539f\u8207\u6b21\u8981\u7fa9\u539f\u7684\u6bd4\u91cd\u3002 3-2 \u8a9e\u610f\u8207\u8a5e\u985e\u6bd4\u91cd\u8a55\u91cf \u6211\u5011\u5c07\u76f8\u4f3c\u5ea6\u6bd4\u91cd\u8a2d\u5b9a w 1 \u70ba 0.8 \u8207 w 2 \u70ba 0.2\uff0cK=1\uff0c\u89c0\u5bdf\u8a9e\u610f\u8207\u8a5e\u985e\u6bd4\u91cd\u7684 \u8b8a\u5316\u5c0d\u6b63\u78ba\u7387\u7684\u5f71\u97ff\u3002 \u8868\u683c 3 \u8a9e\u610f\u8207\u8a5e\u985e\u6bd4\u91cd\u8207\u6b63\u78ba\u7387\u8b8a\u5316\u8868 \u8a9e\u610f\u8207\u8a5e\u985e\u6bd4\u91cd(\u8a9e\u610f,\u8a5e\u985e) \u8a9e\u610f\u76f8\u4f3c\u5ea6\u6bd4\u91cd(w 1 ,w 2 ) \u6b63\u78ba\u7387 (1,0) (0.8,0.2) 57.70% (0.9,0.1) (0.8,0.2)",
"eq_num": "58."
}
],
"section": "",
"sec_num": null
}
],
"back_matter": [],
"bib_entries": {
"BIBREF3": {
"ref_id": "b3",
"title": "Category Guessing for Chinese Unknown Words",
"authors": [
{
"first": "",
"middle": [],
"last": "Chen",
"suffix": ""
},
{
"first": "Ming-Hung",
"middle": [],
"last": "Chao-Jan",
"suffix": ""
},
{
"first": "Keh-Jiann",
"middle": [],
"last": "Bai",
"suffix": ""
},
{
"first": "",
"middle": [],
"last": "Chen",
"suffix": ""
}
],
"year": 1997,
"venue": "Proceedings of the Natural Language Processing Pacific Rim Symposium",
"volume": "",
"issue": "",
"pages": "35--40",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Chen, Chao-Jan, Ming-Hung Bai and Keh-Jiann Chen. \"Category Guessing for Chinese Unknown Words,\" Proceedings of the Natural Language Processing Pacific Rim Symposium, 1997, pp. 35-40.",
"links": null
},
"BIBREF4": {
"ref_id": "b4",
"title": "Unknown Word Detection for Chinese by a Corpus-based Learning Method",
"authors": [
{
"first": "Keh-Jiann",
"middle": [],
"last": "Chen",
"suffix": ""
},
{
"first": "Ming-Hong",
"middle": [],
"last": "Bai",
"suffix": ""
}
],
"year": 1998,
"venue": "Computational Linguistics and Chinese Language Processing",
"volume": "",
"issue": "",
"pages": "27--44",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Chen, Keh-Jiann and Ming-Hong Bai. \"Unknown Word Detection for Chinese by a Corpus-based Learning Method,\" Computational Linguistics and Chinese Language Processing vol3 no. 1, 1998, pp. 27-44.",
"links": null
},
"BIBREF5": {
"ref_id": "b5",
"title": "Knowledge Extraction for Identification of Chinese Organization Names",
"authors": [],
"year": 2000,
"venue": "Proceedings of the second Chinese Language Processing Workshop",
"volume": "",
"issue": "",
"pages": "15--21",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "---. \"Knowledge Extraction for Identification of Chinese Organization Names,\" Proceedings of the second Chinese Language Processing Workshop, 2000, pp. 15-21.",
"links": null
},
"BIBREF6": {
"ref_id": "b6",
"title": "Mandarin Chinese: A Functional Reference Grammar",
"authors": [
{
"first": "Charles",
"middle": [],
"last": "Li",
"suffix": ""
},
{
"first": "Sandra",
"middle": [],
"last": "Thompson",
"suffix": ""
}
],
"year": 1981,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Li, Charles and Sandra Thompson. \"Mandarin Chinese: A Functional Reference Grammar\". Berkeley: University of California Press, 1981.",
"links": null
},
"BIBREF7": {
"ref_id": "b7",
"title": "Using Information Content to Evaluate Semantic Similarity in a Taxonomy",
"authors": [
{
"first": "Philip",
"middle": [],
"last": "Resnik",
"suffix": ""
}
],
"year": 1995,
"venue": "Proceedings of the 14th International Joint Conference on Artificial Intelligence",
"volume": "",
"issue": "",
"pages": "448--453",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Resnik, Philip. \"Using Information Content to Evaluate Semantic Similarity in a Taxonomy,\" Proceedings of the 14th International Joint Conference on Artificial Intelligence, 1995, pp. 448-453.",
"links": null
},
"BIBREF8": {
"ref_id": "b8",
"title": "Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language",
"authors": [],
"year": 1998,
"venue": "Journal of Artificial Intelligence Research XI",
"volume": "",
"issue": "",
"pages": "95--130",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "---. \"Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language,\" Journal of Artificial Intelligence Research XI, 1998, pp. 95-130.",
"links": null
},
"BIBREF9": {
"ref_id": "b9",
"title": "Measuring Verbal Similarity",
"authors": [
{
"first": "Philip",
"middle": [],
"last": "Resnik",
"suffix": ""
},
{
"first": "Mona",
"middle": [],
"last": "Diab",
"suffix": ""
}
],
"year": 2000,
"venue": "",
"volume": "",
"issue": "",
"pages": "",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Resnik, Philip and Mona Diab. Measuring Verbal Similarity. Technical Report: LAMP-TR-047//UMIACS-TR-2000-40/CS-TR-4149/MDA-9049-6C-1250. University of Maryland, College Park, 2000.",
"links": null
},
"BIBREF10": {
"ref_id": "b10",
"title": "A Corpus-Based Analysis of Mandarin Nominal Root Compound",
"authors": [
{
"first": "Sproat",
"middle": [],
"last": "Richard",
"suffix": ""
},
{
"first": "Shilin",
"middle": [],
"last": "Shih",
"suffix": ""
}
],
"year": 1996,
"venue": "Journal of East Asian Linguistics",
"volume": "5",
"issue": "",
"pages": "49--71",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Sproat Richard and Shilin Shih. \"A Corpus-Based Analysis of Mandarin Nominal Root Compound,\" Journal of East Asian Linguistics 5, 1996, pp. 49-71.",
"links": null
},
"BIBREF11": {
"ref_id": "b11",
"title": "Coping with Ambiguity and Unknown Words through Probalistic Model",
"authors": [
{
"first": "Ralph",
"middle": [],
"last": "Weischedel",
"suffix": ""
},
{
"first": "Marie",
"middle": [],
"last": "Meteer",
"suffix": ""
},
{
"first": "Richard",
"middle": [],
"last": "Schwartz",
"suffix": ""
},
{
"first": "Lance",
"middle": [],
"last": "Ramshaw",
"suffix": ""
},
{
"first": "Jeff",
"middle": [],
"last": "Palmucci",
"suffix": ""
}
],
"year": 1993,
"venue": "Computational Linguistics",
"volume": "19",
"issue": "",
"pages": "359--382",
"other_ids": {},
"num": null,
"urls": [],
"raw_text": "Weischedel, Ralph, Marie Meteer, Richard Schwartz, Lance Ramshaw and Jeff Palmucci. \"Coping with Ambiguity and Unknown Words through Probalistic Model,\" Computational Linguistics 19, 1993, pp. 359-382.",
"links": null
}
},
"ref_entries": {
"TABREF0": {
"type_str": "table",
"content": "<table><tr><td>\u4eca\u7121\u6cd5\u63d0\u9ad8\u6b63\u78ba\u7387\u7684\u4e3b\u56e0\u70ba\u52d5\u8a5e\u7e41\u8907\u7684\u5167\u90e8\u7d50\u69cb\u3002 \u6211\u5011\u7684\u76ee\u6a19\u70ba\u5c07\u52d5\u8a5e\u81ea\u52d5\u5206\u985e\u5230\u3197\u7814\u9662\u8a5e\u5eab\u5c0f\u7d44(1993)\u7684\u8a5e\u985e\u67b6\u69cb\u3196\uff0c\u52d5\u8a5e \u5011\u7684\u672a\u77e5\u52d5\u8a5e\u3002\u672a\u77e5\u52d5\u8a5e\u7684\u7b2c\u3193\u500b\u7d44\u6210\u6210\u5206\u8207\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u4f8b\u5b50\u76f8\u540c\u90fd\u70ba\u300c\u5b8c\u300d \uff0c \u4e8b\u300d \u3001 \u300c\u5b78\u300d\u8207\u300c\u6559\u80b2\u300d\u3194\u500b\u7fa9\u539f\u5b9a\u7fa9\u800c\u6210\uff0c\u5728\u77e5\u7db2\u6a19\u8a18\u7fa9\u539f\u7684\u898f\u5247\u3197\uff0c\u5728\u8a5e\u689d\u7684 1-3 \u8a9e\u6599\u5206\u6790\u8207\u8655\u7406 \u56e0\u6b64\u6211\u5011\u50c5\u9700\u8981\u5f97\u77e5\u300c\u8b1b\u300d\u8207\u300c\u5531\u300d\u7684\u76f8\u4f3c\u5ea6\uff0c\u82e5\u300c\u8b1b\u300d\u8207\u300c\u5531\u300d\u5206\u5c6c\u7684\u8a5e\u985e\u76f8 \u6240\u6709\u5b9a\u7fa9\u7fa9\u539f\u3197\uff0c\u7b2c\u3192\u500b\u7fa9\u539f\u3192\u5b9a\u662f\u4e3b\u8981\u610f\u7fa9\u5206\u985e\uff0c\u5f62\u6210\u6982\u5ff5\u9593\u7684\u3196\u3198\u4f4d\u95dc\u4fc2</td><td/></tr><tr><td>\u7684\u8a5e\u985e\u5206\u985e\u5171\u6709 15 \u985e\uff0c\u4f46\u4e26\u975e\u6bcf\u3192\u985e\u90fd\u5177\u6709\u5b73\u751f\u6027\u3002\u6709\u4e9b\u985e\u5225\u5982\u529f\u80fd\u8a5e\u3192\u822c\uff0c \u6211\u5011\u5728\u6b64\u4ecb\u7d39\u672a\u77e5\u52d5\u8a5e\u7684\u7279\u6027\u8207\u53ef\u731c\u6e2c\u672a\u77e5\u52d5\u8a5e\u8a5e\u985e\u7684\u53ef\u80fd\u56e0\u7d20\u3002\u9996\u5148\uff0c\u8a0e \u4f3c\u5ea6\u9ad8\uff0c\u5247\u8868\u793a\u300c\u8b1b\u300d\u8207\u300c\u5531\u300d\u7684\u7d50\u69cb\u985e\u4f3c\uff1b\u82e5\u300c\u8b1b\u300d\u8207\u300c\u5531\u300d\u7684\u8a9e\u610f\u76f8\u4f3c\u7a0b\u5ea6 (is-a relation)\uff0c\u7b2c\u3193\u500b\u4ee5\u5f8c\u7684\u7fa9\u539f\u70ba\u6b21\u8981\u5340\u5206\u8207\u8a5e\u5f59\u4e4b\u9593\u7684\u95dc\u4fc2\u5c31\u4e0d\u78ba\u5b9a\uff0c\u4f9d\u7167</td><td/></tr><tr><td>\u5c6c\u65bc\u5c01\u9589\u6027\u8a5e\u985e\uff0c\u5c01\u9589\u6027\u8a5e\u985e\u70ba\u8a72\u5206\u985e\u3197\u7684\u8a5e\u5f59\u4e0d\u6703\u589e\u52a0\uff0c\u800c\u5728\u3197\u7814\u9662\u8a5e\u5eab\u5c0f\u7d44 \u8ad6\u672a\u77e5\u52d5\u8a5e\u7684\u7279\u6027\u3002\u672a\u77e5\u52d5\u8a5e\u70ba\u8907\u5408\u8a5e\uff0c\u901a\u5e38\u7531\u6578\u500b\u5177\u6709\u5b73\u751f\u6027\u7684\u8a5e\u57fa\u6240\u7d44\u6210\uff0c \u9ad8\u7684\u8a71\uff0c\u5247\u300c\u5531\u5b8c\u300d\u7684\u52d5\u8a5e\u5206\u985e\u5247\u5f88\u53ef\u80fd\u8207\u300c\u8b1b\u5b8c\u300d\u76f8\u540c\u3002 \u77e5\u7db2\u6a19\u8a18\u6c7a\u5b9a\u3002\u8a08\u7b97\u5169\u500b\u8a5e\u689d\u9593\u76f8\u4f3c\u5ea6\u6642\u4e3b\u8981\u7fa9\u539f\u8207\u6574\u500b\u8a5e\u5f59\u4e4b\u9593\u7684\u95dc\u4fc2\u5341\u5206\u91cd</td><td/></tr><tr><td>\u7684\u5206\u985e\u3197 15 \u985e\u3197\u6709 9 \u985e\u662f\u5177\u6709\u5b73\u751f\u6027\u7684\u5206\u985e\uff1b\u9019 9 \u985e\u5206\u985e\u3197\u7684\u52d5\u8a5e\u8a5e\u5f59\uff0c\u6703\u96a8 \u672c\u8eab\u8a9e\u8a00\u5177\u6709\u9ad8\u900f\u660e\u6027\u3002\u4f8b\u5982\uff0c\u672a\u77e5\u52d5\u8a5e\u300c\u6c42\u65b0\u300d\u8207\u300c\u8b1b\u932f\u300d\u76f8\u5c0d\u65bc\u5217\u5165\u8fad\u5178\u3197 \u4f7f\u7528\u76f8\u4f3c\u6cd5\u7684\u597d\u8655\u5728\u65bc\u76f8\u4f3c\u6cd5\u6240\u5c0b\u627e\u7684\u7684\u76f8\u4f3c\u8a5e\uff0c\u82e5\u76f8\u4f3c\u5ea6\u9ad8\u7684\u8a71\uff0c\u4e0d\u50c5\u53ef \u8981\uff0c\u5fc5\u9808\u8207\u5176\u4ed6\u7684\u6b21\u8981\u7fa9\u539f\u5206\u958b\u8a08\u7b97\u3002\u56e0\u6b64</td><td/></tr><tr><td>\u8457\u8a9e\u6599\u5eab\u7684\u589e\u9577\u800c\u589e\u591a\uff0c\u6211\u5011\u5e0c\u671b\u5c07\u672a\u77e5\u52d5\u8a5e\u81ea\u52d5\u5206\u985e\u5230\u9019 9 \u985e\u52d5\u8a5e\u5206\u985e\u3197\uff0c\u9019 \u4e5d\u985e\u70ba\u52d5\u4f5c\u4e0d\u53ca\u7269\u52d5\u8a5e(VA)\u3001\u52d5\u4f5c\u53ca\u7269\u52d5\u8a5e(VC)\u3001\u52d5\u4f5c\u53ca\u7269\u52d5\u8a5e\uff0b\u319e\u65b9\u8cd3\u8a9e (VCL)\u3001\u52d5\u4f5c\u96d9\u8cd3\u52d5\u8a5e(VD)\u3001\u52d5\u4f5c\u53e5\u8cd3\u52d5\u8a5e(VE)\u3001\u5206\u985e\u52d5\u8a5e(VG)\u3001\u72c0\u614b\u4e0d\u53ca\u7269\u52d5 \u8a5e(VH)\u3001\u72c0\u614b\u4f7f\u52d5\u52d5\u8a5e(VHC)\u3001\u72c0\u614b\u53ca\u7269\u52d5\u8a5e(VJ)\u3002 \u7684\u300c\u5fd0\u5fd1\u300d \u3001 \u300c\u4fb7\u4fc3\u300d\u9019\u3192\u985e\u7684\u8a5e\u5f59\u591a\u5177\u6709\u8a9e\u610f\u900f\u660e\u6027\uff0c\u4e26\u4e14\u53ef\u4ee5\u5f9e\u5176\u7d44\u6210\u6210\u5206\u9810 \u6e2c\u51fa\u8a72\u8a5e\u7684\u8a9e\u610f\u3002 \u5176\u6b21\uff0c\u6211\u5011\u8a8d\u70ba\u6709\u5169\u500b\u56e0\u7d20\u53ef\u9810\u6e2c\u672a\u77e5\u52d5\u8a5e\u7684\u5206\u985e\u3002\u3192\u3001\u8a9e\u610f\u3002\u8a9e\u610f\u76f8\u8fd1\u7684 \u8a5e\u5f59\uff0c\u6240\u5c6c\u7684\u8a5e\u985e\u61c9\u985e\u4f3c\u3002\u6211\u5011\u5c07\u540c\u7fa9\u8a5e\u8a5e\u6797\u3197\u7684\u8a9e\u610f\u985e\u8207\u3197\u7814\u9662\u8a5e\u5eab\u5c0f\u7d44(1993) \u4ee5\u9810\u6e2c\u8a5e\u985e\u5206\u985e\uff0c\u540c\u6642\u4e5f\u53ef\u4ee5\u9810\u6e2c\u8a9e\u610f\u8207\u7d50\u69cb\u5206\u985e\u3002\u7576\u5169\u500b\u8a5e\u5f59\u76f8\u4f3c\u5ea6\u9ad8\u6642\uff0c\u8868 \u793a\u9019\u5169\u500b\u8a5e\u5f59\u7684\u8a5e\u985e\u3001\u8a9e\u610f\u985e\u8207\u7d50\u69cb\u5fc5\u5b9a\u76f8\u4f3c\u3002 \u6211\u5011\u5728\u672c\u7bc0\u3197\u9996\u5148\u4ecb\u7d39\u8a9e\u610f\u8207\u8a5e\u985e\u76f8\u4f3c\u5ea6\u7684\u6e2c\u91cf\u65b9\u6cd5\uff0c\u63a5\u3198\u4f86\u8aaa\u660e\u76f8\u4f3c\u8a5e\u7684 \u9078\u53d6\u8207\u672a\u77e5\u52d5\u8a5e\u8a5e\u985e\u7684\u9810\u6e2c\u3002 ( ) ( y 2 x 1 Entry Word , Entry Word core HowNetSimS \u2212 \u2212 ) ( )( ( ) m y, y,2 n x, x,2 2 y,1 x,1 1 ...Sem Sem , ...Sem Sem core SecondaryS * w Sem Sem re PrimarySco * w + \u2229 = )</td><td/></tr><tr><td>\u8a5e\u985e\u4f5c\u5c0d\u61c9\uff0c\u3197\u7814\u9662\u8a5e\u5eab\u5c0f\u7d44\u8a5e\u985e\u6709 45 \u985e\u3002\u5e73\u5747\u4f86\u8aaa\uff0c\u540c\u7fa9\u8a5e\u8a5e\u6797\u3192\u500b\u8a9e\u610f\u985e</td><td/></tr><tr><td>1-2 \u7814\u7a76\u65b9\u6cd5 \u50c5\u5c0d\u61c9\u5230\u8a5e\u5eab\u5c0f\u7d44 1.97 \u7a2e\u8a5e\u985e\uff0c\u5373\u3192\u500b\u8a9e\u610f\u985e\u3197\u7684\u8a5e\u5f59\u5171\u6709\u7684\u8a5e\u985e\u6578\u91cf\u3002\u56e0\u6b64 \u6211\u5011\u8a8d\u70ba\u8a9e\u610f\u56e0\u7d20\u53ef\u5de6\u53f3\u8a5e\u5f59\u7684\u8a5e\u985e\u3002\u3193\u3001\u7d50\u69cb\u3002\u7d50\u69cb\u901a\u5e38\u6703\u9650\u5b9a\u7d44\u6210\u7684\u8a5e\u985e\uff0c \u77e5\u7db2\u3197\u6709\u63cf\u8ff0\u7fa9\u539f\u8207\u7fa9\u539f\u4e4b\u9593\u7684\u968e\u5c64\u95dc\u4fc2\u7684\u5206\u985e\u6a39\uff0c\u6211\u5011\u5728\u9019\u908a\u5229\u7528\u63cf\u8ff0 2-2 \u76f8\u4f3c\u5ea6\u6e2c\u91cf \u7fa9\u539f\u4e4b\u9593\u95dc\u4fc2\u7684\u5206\u985e\u6a39\u4f86\u5e6b\u52a9\u6211\u5011\u8a08\u7b97\u7fa9\u539f\u9593\u7684\u76f8\u4f3c\u5ea6\u3002\u9673\u514b\u5065\u3001\u9673\u8d85\u7136</td><td/></tr><tr><td>\u672c\u8ad6\u6587\u3197\u672a\u77e5\u8a5e\u7684\u5b9a\u7fa9\u70ba\u4e0d\u5b58\u5728\u8fad\u5178\u3197\u7684\u8a5e\u5f59\u3002\u9673\u514b\u5065\u3001\u9673\u8d85\u7136(1997)\u5206\u6790 \u82e5\u7d50\u69cb\u70ba\"VC+Na\"\u7684\u672a\u77e5\u52d5\u8a5e\uff0c\u901a\u5e38\u6703\u7d44\u6210 VA \u8a5e\u985e\uff0c\u56e0\u70ba\u5728\u9019\u500b\u672a\u77e5\u52d5\u8a5e\u7684\u5167 \u5728\u672c\u8ad6\u6587\u3197\u6211\u5011\u4f7f\u7528\u77e5\u7db2\u4f5c\u70ba\u8a9e\u610f\u6e2c\u91cf\u7684\u5de5\u5177\uff0c\u3197\u592e\u7814\u7a76\u9662\u3197\u6587\u53e5\u7d50\u69cb\u6a39\u6e2c (1997:270)\u8a8d\u70ba\u5169\u500b\u8a9e\u610f\u985e\u7684\u76f8\u4f3c\u5ea6\u5728\u65bc\u5169\u500b\u8a9e\u610f\u985e\u5728\u5206\u985e\u6a39\u4ea4\u96c6\u7bc0\u9ede\u7684\u8a9e\u610f\u8a0a</td><td/></tr><tr><td>\u672a\u77e5\u8a5e\u7684\u7a2e\u985e\u70ba\u5169\u7a2e\uff0c\u7b2c\u3192\u7a2e\u70ba\u5c01\u9589\u6027\uff0c\u9019\u3192\u985e\u578b\u96d6\u7136\u5728\u6578\u91cf\u3196\u53ef\u80fd\u70ba\u7121\u6578\u500b\uff0c \u90e8\u7d50\u69cb\u3197\u5df2\u7d93\u51fa\u73fe\u4e86\u3192\u500b\u666e\u901a\u540d\u8a5e(Na)\u4f86\u6eff\u8db3\u524d\u9762\u7684\u52d5\u4f5c\u53ca\u7269\u52d5\u8a5e(VC)\u6240\u8981\u6c42 \u91cf\u8a5e\u985e\u76f8\u4f3c\u5ea6\uff0c\u4ecb\u7d39\u5982\u3198\u3002 \u606f\u91cf(Information Content)\uff0c\u5c07\u6574\u500b\u8a5e\u5206\u985e\u67b6\u69cb\u770b\u6210\u3192\u500b\u8a0a\u606f\u7cfb\u7d71\uff0c\u3192\u500b\u8a9e\u610f\u985e</td><td/></tr><tr><td>\u4f46\u662f\u53ef\u7528\u898f\u5247\u8a9e\u6cd5(Regular Expression)\u4f86\u7522\u751f\u8207\u8fa8\u8b58\uff0c\u5982\uff1a\u897f\u5143\u3192\u4e5d\u4e5d\u4e5d\u5e74(\u6642 \u7684\u8ad6\u5143\uff0c\u5728\u9019\u7a2e\u60c5\u5f62\u3198\u901a\u5e38\u6703\u5f62\u6210\u4e0d\u53ca\u7269\u52d5\u8a5e\uff0c\u56e0\u6b64\u6211\u5011\u8a8d\u70ba\u7d50\u69cb\u6703\u5f71\u97ff\u5230\u52d5\u8a5e \u3192\u3001\u77e5\u7db2\u70ba\u3192\u96d9\u8a9e(\u3197\u6587\u3001\u82f1\u6587)\u7684\u77e5\u8b58\u6027\u8fad\u5178\uff0c\u7531\u8463\u632f\u6771\u8207\u8463\u5f37\u7de8\u64b0\u5b8c\u6210\u6536 Sem (\u76f8\u7576\u65bc\u77e5\u7db2\u3197\u7684\u7fa9\u539f)\u7684\u8a0a\u606f\u91cf\u5b9a\u7fa9\u70ba Entropy(System)-Entropy(Sem)\u3002\u6211\u5011</td><td/></tr><tr><td>\u9593)\u3001\u3192\u5343\u5169\u767e\u4e03\u5341\u3193(\u6578\u5b57)\u3001\u3193\u4e03\u516b\u516b\u3194\u4e03\u4e5d\u4e5d(\u96fb\u8a71)\u7b49\u3002\u7b2c\u3193\u985e\u5247\u70ba\u958b\u653e\u6027\uff0c \u7684\u8a5e\u985e\u3002 \u9304\u7d04\u5341\u3192\u842c\u689d\u8a5e\u689d\uff0c\u77e5\u7db2\u7cfb\u7d71\u3197\u5305\u542b\u6709\u3197\u82f1\u96d9\u8a9e\u77e5\u8b58\u8fad\u5178\u3001\u3197\u6587\u7c21\u9ad4\u77e5\u8b58\u8fad\u5178\u3001 \u5728\u9019\u908a\u4f7f\u7528\u9673\u514b\u5065\u3001\u9673\u8d85\u7136(1997)\u8a08\u7b97\u8a9e\u610f\u8a0a\u606f\u91cf\u7684\u65b9\u6cd5\u4f86\u8a08\u7b97\u77e5\u7db2\u3197\u5404\u7fa9\u539f\u7684</td><td/></tr><tr><td>\u9019\u3192\u985e\u7684\u672a\u77e5\u8a5e\u5f88\u96e3\u7528\u898f\u5247\u8a9e\u6cd5\u4f86\u8868\u9054\uff0c\u8907\u5408\u8a5e\u5373\u5c6c\u9019\u3192\u985e\u3002\u767d\u660e\u5b8f\u3001\u9673\u8d85\u7136\u8207 \u5728\u672c\u7bc7\u8ad6\u6587\u3197\u6211\u5011\u5229\u7528\u9019\u4e9b\u7dda\u7d22\u5c0b\u627e\u8207\u672a\u77e5\u52d5\u8a5e\u76f8\u4f3c\u7684\u8a5e\u5f59\uff0c\u4f86\u9810\u6e2c\u672a\u77e5\u52d5 \u3197\u6587\u7e41\u9ad4\u77e5\u8b58\u8fad\u5178\u3001\u6982\u5ff5\u7279\u5fb5\u3001\u52d5\u614b\u89d2\u8272\u8207\u5c6c\u6027\u3001\u8a5e\u985e\u8868\u3001\u53cd\u7fa9\u95dc\u4fc2\u8868\u3001\u5c0d\u7fa9\u95dc \u8a0a\u606f\u91cf\u3002 1. \u7dd2\u8ad6 \u9673\u514b\u5065(1998)\u5728\u5206\u6790\u3197\u7814\u9662\u5e73\u8861\u8a9e\u6599\u5eab\u5f8c\u6b78\u7d0d\u51fa\u672a\u77e5\u8a5e\u4e3b\u8981\u7684\u5206\u985e\u70ba\u7565\u8a9e\u3001\u5c08\u6709 \u8a5e\u6240\u5c6c\u7684\u8a5e\u985e\u3002 \u4fc2\u8868\u3001\u6a19\u793a\u7b26\u865f\u8207\u8aaa\u660e\u3001\u77e5\u7db2\u7ba1\u7406\u7a0b\u5e8f\u7b49\u3002\u6211\u5011\u5728\u672c\u7bc0\u7576\u3197\u5c07\u4ecb\u7d39\u5982\u4f55\u4f7f\u7528\u77e5\u7db2 \u77e5\u7db2\u3197\u5169\u500b\u7fa9\u539f\u7684\u76f8\u4f3c\u5ea6\u70ba\u9019\u5169\u500b\u7fa9\u539f\u6240\u4ea4\u96c6\u7bc0\u9ede\u7684\u8a9e\u610f\u8a0a\u606f\u91cf\uff0c\u6240\u5f97\u5230\u8a9e</td><td/></tr><tr><td>\u81ea\u7136\u8a9e\u8a00\u8655\u7406\u3197\u91cd\u8981\u7684\u6b65\u9a5f\u662f\u5c07\u3197\u6587\u6587\u4ef6\u65b7\u8a5e\u4e26\u9644\u52a0\u8a5e\u985e\u6a19\u8a18\uff1b\u5728\u65b7\u8a5e\u6a19\u8a18 \u540d\u8a5e\u3001\u884d\u751f\u8a5e\u3001\u8907\u5408\u8a5e\u8207\u6578\u5b57\u578b\u8907\u5408\u8a5e\u3002 \u8a08\u7b97\u8a9e\u610f\u76f8\u4f3c\u5ea6\u8207\u8a55\u91cf\u65b9\u6cd5\u3002 \u610f\u8a0a\u606f\u91cf\u8d8a\u9ad8\u8868\u793a\u9019\u5169\u500b\u7fa9\u539f\u8d8a\u76f8\u4f3c\uff0c\u56e0\u6b64\u7b2c\u3192\u90e8\u4efd\u7684\u76f8\u4f3c\u5ea6\u5b9a\u7fa9\u5982\u3198\uff1a</td><td/></tr><tr><td>\u7684\u904e\u7a0b\u3197\u6703\u9047\u5230\u7684\u3192\u500b\u554f\u984c\u70ba\u672a\u77e5\u8a5e\u7684\u5b58\u5728\u3002\u73fe\u884c\u7684\u65b7\u8a5e\u6a19\u8a18\u7cfb\u7d71\u4ee5\u8fad\u5178\u70ba\u57fa\u790e \u8f14\u4ee5\u69cb\u8a5e\u7684\u898f\u5247\u8a0a\u606f\u9032\u884c\u65b7\u8a5e\u6a19\u8a18\uff0c\u4f46\u56e0\u70ba\u8a9e\u8a00\u7684\u7279\u6027\u4e4b\u3192\u300c\u7121\u7aae\u76e1\u7684\u5275\u9020\u529b\u300d \uff0c \u7121\u6cd5\u7aae\u8209\u51fa\u6240\u6709\u7684\u8a5e\u5f59\uff1b\u3192\u672c\u597d\u7684\u8fad\u5178\u4e5f\u4e0d\u61c9\u8a72\u7121\u6b62\u76e1\u7684\u64f4\u5927\u6240\u6536\u9304\u7684\u8a5e\u5f59\uff0c\u56e0 \u6b64\u5982\u4f55\u8fa8\u8b58\u8655\u7406\u8fad\u5178\u3197\u4e0d\u5b58\u5728\u7684\u8a5e\u5f59\u5c31\u6210\u4e86\u3192\u500b\u91cd\u8981\u7684\u8ab2\u984c\u3002 \u672a\u77e5\u52d5\u8a5e\u901a\u5e38\u70ba\u8907\u5408\u8a5e\uff0c\u7531\u5169\u500b\u4ee5\u3196\u7684\u7d44\u6210\u6210\u5206\u7d44\u5408\u800c\u6210\uff0c\u9019\u7a2e\u7d44\u6210\u6210\u5206\u6211 \u5011\u7a31\u70ba\u8a5e\u57fa(base) 2 \u3002\u8d99\u5143\u4efb(1968)\u3001Li \u8207 Thompson (1981)\u8207\u6e6f\u5ef7\u6c60(1988)\u63d0\u53ca\u6f22 \u8a9e\u7684\u8907\u5408\u8a5e\u5177\u6709\u7279\u5b9a\u7684\u5167\u90e8\u53e5\u6cd5\u7d50\u69cb\uff1b\u5982\uff1a \u300c\u6b3a\u6575\u300d \uff0c\u7531\u300c\u6b3a\u300d\u8207\u300c\u6575\u300d\u9019\u5169\u500b\u8a5e \u57fa\u7d44\u6210\uff0c\u5169\u500b\u8a5e\u57fa\u4e4b\u9593\u7684\u95dc\u4fc2\u70ba\u52d5\u8cd3\u7d50\u69cb\u3002\u96d6\u7136\u8a5e\u57fa\u662f\u6709\u9650\u7684\uff0c\u4f46\u662f\u8a5e\u57fa\u8207\u8a5e\u57fa 2. \u5be6\u9a57\u65b9\u6cd5 \u6211\u5011\u5229\u7528\u76f8\u4f3c\u6cd5\u4f86\u5224\u65b7\u52d5\u8a5e\u7684\u5206\u985e\uff0c\u5c0b\u627e\u672a\u77e5\u52d5\u8a5e\u7684\u76f8\u4f3c\u8a5e\uff0c\u8a08\u7b97\u672a\u77e5\u52d5\u8a5e \u8207\u76f8\u4f3c\u8a5e\u4e4b\u9593\u7684\u76f8\u4f3c\u5ea6\uff0c\u518d\u5c07\u9019\u4e9b\u76f8\u4f3c\u8a5e\u4f9d\u7167\u8a5e\u985e\u5206\u7d44\u3002\u5f9e\u6bcf\u500b\u8a5e\u985e\u7576\u3197\u53d6\u51fa K \u3193\u3001\u3197\u592e\u7814\u7a76\u9662\u3197\u6587\u53e5\u7d50\u69cb\u6a39\u8cc7\u6599\u5eab 1.0 \u3197\u5305\u542b\u4e86\u5341\u500b\u6a94\u6848\uff0c\u3194\u842c\u516b\u5343\u4e03\u767e \u3193\u5341\u4e94\u68f5\u3197\u6587\u7d50\u69cb\u6a39\uff0c\u542b\u6709\u3193\u5341\u3194\u842c\u4e5d\u5343\u4e94\u767e\u3194\u5341\u3193\u500b\u8a5e\u8a5e\u5f59\uff0c\u6bcf\u3192\u53e5\u7d50\u69cb\u6a39\uff0c \u6a19\u793a\u6f22\u8a9e\u53e5\u6cd5\u8207\u8a9e\u610f\u8a0a\u606f\uff0c\u8a5e\u985e\u6a19\u8a18\u8207\u65b7\u8a5e\u6a19\u8a18\u7cfb\u7d71\u3195\u5341\u4e94\u500b\u6a19\u8a18\u4e0d\u540c\uff0c\u7d50\u69cb\u6a39 \u3197\u7684\u6a19\u8a18\u662f\u7531\u3195\u5341\u4e94\u500b\u6a19\u8a18\u7d30\u5206\u800c\u6210\u3002\u5728\u672c\u7bc0\u3197\u6211\u5011\u5229\u7528\u3197\u7814\u9662\u3197\u6587\u53e5\u7d50\u69cb\u6a39\u6e2c ( ) ( ) ( ) ( ( ) ( ) ( System /Entropy Sem Sem Entropy System Entropy ) System /Entropy Sem Sem nContent Informatio ) Sem Sem re PrimarySco</td><td/></tr><tr><td>\u7684\u7d44\u5408\u6578\u91cf\u9f90\u5927\uff0c\u4e14\u7d44\u5408\u6210\u5206\u9593\u7684\u8a9e\u610f\u95dc\u4fc2\u8907\u96dc\uff0c\u56e0\u6b64\u9020\u6210\u4e86\u6211\u5011\u7121\u6cd5\u5c07\u6240\u6709\u7684 \u500b\u76f8\u4f3c\u8a5e\u51fa\u4f86\uff0c\u5c07\u9019\u4e9b\u76f8\u4f3c\u8a5e\u7684\u5206\u6578\u4e88\u4ee5\u5e73\u5747\uff0c\u5f97\u5230\u672a\u77e5\u52d5\u8a5e\u5230\u6bcf\u500b\u8a5e\u985e\u7684\u5e73\u5747 \u91cf\u8a5e\u985e\u7684\u76f8\u4f3c\u5ea6\u3002</td><td/></tr><tr><td>\u672a\u77e5\u52d5\u8a5e\u6536\u9304\u9032\u5b57\u5178\u3197\u3002 \u8ddd\u96e2\uff0c\u672a\u77e5\u52d5\u8a5e\u7684\u8a5e\u985e\u5373\u8207\u5176\u8ddd\u96e2\u6700\u76f8\u8fd1\u7684\u8a5e\u985e\u3002 1-1 \u7814\u7a76\u52d5\u6a5f\u8207\u76ee\u6a19 \u524d\u319f\u5c0d\u65bc\u672a\u77e5\u8a5e\u7684\u63a2\u8a0e\u91cd\u9ede\u96c6\u3197\u5728\u540d\u8a5e\u7d30\u76ee\u7684\u8fa8\u8a8d\u3196\uff0c\u5982\u7d44\u7e54\u540d\u3001\u319f\u540d\u3001\u319e \u540d\u8fa8\u8b58\u7b49(\u674e\u632f\u660c(1993)\uff0c\u674e\u632f\u660c\u3001\u674e\u5fa1\u74bd\u8207\u9673\u4fe1\u5e0c(1994)\u319f\u540d\u8fa8\u8b58\u7b49\u7b49)\u3002\u50c5\u6709 \u5728\u672c\u8ad6\u6587\u3197\u6211\u5011\u5229\u7528\u76f8\u4f3c\u6cd5\u4f86\u5224\u65b7\u52d5\u8a5e\u7684\u5206\u985e\uff0c\u5c0b\u627e\u672a\u77e5\u52d5\u8a5e\u7684\u76f8\u4f3c\u8a5e\uff0c\u8a08 2-2-1 \u8a9e\u610f\u76f8\u4f3c\u5ea6\u6e2c\u91cf \u7b97\u672a\u77e5\u52d5\u8a5e\u8207\u76f8\u4f3c\u8a5e\u4e4b\u9593\u7684\u76f8\u4f3c\u5ea6\uff0c\u518d\u5c07\u9019\u4e9b\u76f8\u4f3c\u8a5e\u4f9d\u7167\u8a5e\u985e\u5206\u7d44\u3002\u5f9e\u6bcf\u500b\u8a5e\u985e \u7576\u3197\u53d6\u51fa K \u500b\u76f8\u4f3c\u8a5e\u51fa\u4f86\uff0c\u5c07\u9019\u4e9b\u76f8\u4f3c\u8a5e\u7684\u5206\u6578\u4e88\u4ee5\u5e73\u5747\uff0c\u5f97\u5230\u672a\u77e5\u52d5\u8a5e\u5230\u6bcf \u500b\u8a5e\u985e\u7684\u5e73\u5747\u8ddd\u96e2\uff0c\u672a\u77e5\u52d5\u8a5e\u7684\u8a5e\u985e\u5373\u8207\u5176\u8ddd\u96e2\u6700\u76f8\u8fd1\u7684\u8a5e\u985e\u3002 \u77e5\u7db2\u7d04\u9078\u7528\u4e86\u3192\u5343\u4e03\u767e\u591a\u500b\u7fa9\u539f\u4f86\u5b9a\u7fa9\u3197\u82f1\u96d9\u8a9e\u77e5\u8b58\u8fad\u5178\u3197\u7684\u6bcf\u500b\u8a5e\uff0c\u4e26\u4e14 2-\u6211\u5011\u5728\u9019\u7bc0\u8aaa\u660e\u5982\u4f55\u4f7f\u7528\u76f8\u4f3c\u6cd5\u4f86\u9810\u6e2c\u52d5\u8a5e\u7684\u5206\u985e\u3002\u672a\u77e5\u52d5\u8a5e\u7684\u7279\u6027\u4e4b\u3192\u70ba \u7d44\u6210\u6210\u5206\u5c6c\u65bc\u5e38\u7528\u8a5e\u4e14\u8a9e\u610f\u660e\u78ba\uff0c\u4f8b\u5982\uff1a\u8a66\u5370\u3001\u8b1b\u5b8c\u3002\u9019\u5169\u500b\u8a5e\u5f59\u90fd\u7121\u6cd5\u5728\u8fad\u5178 \u3197\u67e5\u8a62\u5230\uff0c\u4f46\u6211\u5011\u537b\u5f88\u6e05\u695a\u7684\u53ef\u4ee5\u5f9e\u5b57\u9762\u3196\u5f97\u77e5\u9019\u5169\u500b\u52d5\u8a5e\u7684\u8a9e\u610f\uff0c\u800c\u4e14\u9019\u6a23\u7684 \u5efa\u6709\u63cf\u8ff0\u5404\u500b\u7fa9\u539f\u4e4b\u9593\u7684\u95dc\u4fc2\u7684\u5206\u985e\u6a39\u3002\u4f8b\u5982\uff1a \u300c\u8b80\u66f8\u300d\u3192\u8a5e\u7531\u300c\u5f9e\u4e8b\u300d \u3001 \u300c\u5b78\u300d \u8207\u300c\u6559\u80b2\u300d\u3194\u500b\u7fa9\u539f\u5b9a\u7fa9\u800c\u6210\uff0c\u77e5\u7db2\u3197\u4e26\u6709\u5206\u985e\u6a39\u8868\u793a\u300c\u5f9e\u4e8b\u300d \u3001 \u300c\u5b78\u300d\u8207\u300c\u6559\u80b2\u300d \u3194\u500b\u7fa9\u539f\u4e4b\u9593\u7684\u95dc\u4fc2\u3002 () Chen\u3001Bai \u8207 \u4e4b\u8655\uff0c\u5c07\u6b63\u78ba\u7387\u63d0\u9ad8\u81f3 83.83%\u3002\u5728\u52d5\u8a5e\u8fa8\u8b58\u6b63\u78ba\u7d50\u679c\u4e0d\u9ad8\u7684\u60c5\u6cc1\u3198\uff0c\u672c\u8ad6\u6587\u5c07 \u8655\u7406\u91cd\u5fc3\u653e\u5728\u672a\u77e5\u52d5\u8a5e\u7684\u8fa8\u8b58\u8655\u7406\u3196\uff0c\u4e26\u4e14\u5e0c\u671b\u5c07\u9019\u7a2e\u8655\u7406\u672a\u77e5\u52d5\u8a5e\u7684\u65b9\u6cd5\u5728\u672a \u6839\u64da\u6211\u5011\u5c0d\u672a\u77e5\u52d5\u8a5e\u8a9e\u6599\u7684\u89c0\u5bdf\uff0c\u672a\u77e5\u52d5\u8a5e\u7684\u7d44\u6210\u96d6\u7136\u6709\u3192\u5b9a\u7684\u6a21\u5f0f\uff0c\u4f46\u56e0 \u6b64\u6211\u5011\u5728\u9019\u908a\u5b9a\u7fa9\u5169\u500b\u8a5e Word 1 ,Word 2 \u9593\u7684\u76f8\u4f3c\u5ea6\u76f8\u7b49\u65bc\u5169\u500b\u8a5e\u5404\u5c6c\u7684\u8a5e\u689d\u9593\u6700 2 Sproat \u8207 Shih (1996) \u7a31\u5167\u90e8\u7684\u8655\u7406\u55ae\u4f4d\u70ba\u8a5e\u6839(root)\uff0cChen\u3001Bai \u8207 Chen (1997)\u7a31\u8655\u7406\u7684\u55ae\u4f4d\u70ba \u7d44\u5408\u65b9\u5f0f\u662f\u975e\u5e38\u5177\u6709\u5b73\u751f\u6027\u7684\uff0c\u53ef\u4ee5\u7e7c\u7e8c\u5b73\u751f\u300c\u5531\u5b8c\u300d \u3001 \u300c\u8aaa\u5b8c\u300d\u7b49\u7b49\u5404\u6a23\u7684\u8a5e\u5f59\u3002 \u3192\u822c\u4f86\u8aaa\uff0c\u3192\u500b\u8a5e\u5728\u77e5\u7db2\u3197\u53ef\u80fd\u64c1\u6709\u591a\u500b\u8a5e\u689d\uff0c\u539f\u56e0\u5728\u65bc\u8a5e\u5f59\u7684\u591a\u7fa9\u6027\uff0c\u56e0 ( ) ()</td><td/></tr><tr><td>\u4f86\u53ef\u4ee5\u8f49\u79fb\u8655\u7406\u540d\u8a5e\u8207\u5f62\u5bb9\u8a5e\u3002 \u524d\u7db4(prefix)\u8207\u5f8c\u7db4(suffix)\u3002\u6211\u5011\u5247\u7a31\u8655\u7406\u55ae\u4f4d\u70ba\u8a5e\u57fa(base)\uff0c\u4e26\u63a1\u7528 Katamba (1993:45) \u5c0d\u8a5e\u57fa \u70ba\u8a9e\u8a00\u7684\u8907\u96dc\u5ea6\uff0c\u7121\u6cd5\u5c07\u6240\u6709\u7684\u898f\u5247\u689d\u5217\u51fa\u4f86\u3002\u56e0\u6b64\u6211\u5011\u5728\u9019\u908a\u4f7f\u7528\u76f8\u4f3c\u6cd5\uff0c\u5c07 \u5927\u76f8\u4f3c\u5ea6\u3002</td><td/></tr><tr><td>\u52d5\u8a5e\u4e0d\u7ba1\u5728\u4efb\u4f55\u6587\u6cd5\u7406\u8ad6\u3197\uff0c\u5728\u5256\u6790\u53e5\u5b50\u6642\u90fd\u662f\u4f4d\u65bc\u6700\u3197\u5fc3\u7684\u90e8\u5206\uff0c\u82e5\u52d5\u8a5e \u70ba\u672a\u77e5\u8a5e\uff0c\u52e2\u5fc5\u5c07\u5f71\u97ff\u53e5\u5b50\u5256\u6790\u7684\u6b63\u78ba\u6027\u3002\u73fe\u4ee3\u6f22\u8a9e\u7684\u52d5\u8a5e\u7d50\u69cb\u7e41\u8907\uff0c\u5167\u90e8\u898f\u5247 \u8907\u96dc\uff0c\u82e5\u7121\u8db3\u5920\u7684\u8a9e\u8a00\u8a0a\u606f\u5b8c\u5168\u7121\u6cd5\u5224\u65b7\u5176\u5206\u985e\uff0c\u6211\u5011\u8a8d\u70ba\u52d5\u8a5e\u81ea\u52d5\u5206\u985e\u7814\u7a76\u81f3 \u77e5\u52d5\u8a5e\u8207\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u52d5\u8a5e\u8d8a\u76f8\u4f3c\u6642\uff0c\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u8d8a\u6709\u53ef\u80fd\u5c6c\u65bc\u8207\u5176\u76f8\u4f3c\u52d5\u8a5e (base)\u5728\u6b64\u8655\u6c7a\u5b9a\u4f7f\u7528\u8a5e\u57fa\u70ba\u6211\u5011\u5207\u5272\u7684\u55ae\u4f4d\u7684\u539f\u56e0\u5728\u65bc\u8a5e\u57fa\u7684\u5b9a\u7fa9\u8f03\u8a5e\u6839 (root) \u3001\u8a5e\u5e79 (stem) \u5bec \u6bcf\u500b\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u672a\u77e5\u52d5\u8a5e\u90fd\u7576\u4f5c\u662f\u3192\u689d\u898f\u5247\uff0c\u7576\u6709\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u51fa\u73fe\u6642\uff0c\u5c07\u5176 \u8207\u6240\u6709\u7684\u52d5\u8a5e\u505a\u6bd4\u8f03\uff0c\u6e2c\u91cf\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u8207\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u52d5\u8a5e\u7684\u76f8\u4f3c\u5ea6\uff0c\u65b0\u7684\u672a ( ) ( 2 x 1 2 1 Entry y Word , Entry Word imScore maxHowNetS Word , Word core HowNetSimS \u2212 \u2212 =</td><td>)</td></tr><tr><td>\u9b06\u3002\u672a\u77e5\u52d5\u8a5e\u88ab\u6211\u5011\u65b7\u8a5e\u7cfb\u7d71\u5207\u5206\u51fa\u4f86\u5f88\u591a\u55ae\u4f4d\uff0c\u6211\u5011\u4e26\u4e0d\u78ba\u5b9a\u9019\u4e9b\u55ae\u4f4d\u771f\u6b63\u7684\u610f\u7fa9\uff0c\u56e0\u6b64\u6211\u5011 \u7684\u8a5e\u985e\u3002\u4f8b\u5982\uff1a\u8b1b\u5b8c\u8207\u5531\u5b8c\u3002\u82e5\u300c\u8b1b\u5b8c\u300d\u6211\u5011\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u52d5\u8a5e\uff0c \u300c\u5531\u5b8c\u300d\u70ba\u6211 \u5176\u6b21\uff0c\u6bcf\u3192\u500b\u8a5e\u689d\u53ef\u80fd\u7531\u3192\u5230\u516b\u500b\u7fa9\u539f\u5b9a\u7fa9\u800c\u6210\uff0c\u5982\u300c\u8b80\u66f8\u300d\u3192\u8a5e\u7531\u300c\u5f9e</td><td/></tr><tr><td>\u5e0c\u671b\u9078\u7528\u3192\u500b\u6700\u5bec\u9b06\u7684\u5b9a\u7fa9\u53ef\u4ee5\u6db5\u84cb\u6240\u6709\u88ab\u65b7\u8a5e\u7cfb\u7d71\u6240\u5207\u5206\u7684\u55ae\u4f4d\u3002</td><td/></tr></table>",
"text": "Chen(1997)\u5229\u7528\u524d\u7db4(prefix)\u3001\u5f8c\u7db4(suffix)\u7684\u8a0a\u606f\u8655\u7406\u5168\u90e8\u7684\u672a\u77e5\u8a5e\uff0c \u6b63\u78ba\u7387\u7d04\u70ba 76%\uff0c\u800c\u767d\u660e\u5b8f\u3001\u9673\u8d85\u7136\u8207\u9673\u514b\u5065(1998)\u4f7f\u7528 Chen\u3001Bai \u8207Chen (1997) \u6240\u63d0\u51fa\u7684\u65b9\u6cd5\uff0c\u518d\u5229\u7528\u524d\u5f8c\u6587\u7684\u8a0a\u606f\u4f86\u88dc\u5f37 Chen\u3001Bai \u8207 Chen (1997)\u65b9\u6cd5\u4e0d\u8db3 \u6240\u3198\u5b9a\u7fa9\uff1a\"\u2026a base is any unit whatsoever to which affixes of any kind can be added\u2026.In other words, all roots are bases. Bases are called stems only in the context of inflectional morphology.\" \u6211\u5011",
"num": null,
"html": null
},
"TABREF1": {
"type_str": "table",
"content": "<table><tr><td colspan=\"3\">( Category \u82e5\u63a1\u7528\u9019\u7a2e\u65b9\u6cd5\u5fc5\u9808\u8a08\u7b97\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u6bcf\u3192\u500b\u8a5e\u5f59\u8207\u6211\u5011\u672a\u77e5\u52d5\u8a5e\u7684\u76f8\u4f3c ) j i j i j i Category Category Category Category Category ore CategorySc , \u2022 = * \u5ea6\uff0c\u5c07\u6703\u6d6a\u8cbb\u8a31\u591a\u4e0d\u5fc5\u8981\u7684\u8a08\u7b97\u6642\u9593\uff0c\u56e0\u6b64\u50c5\u5c31\u8a13\u7df4\u8a9e\u6599\u3197\u8207\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u524d\u8a5e</td></tr><tr><td colspan=\"3\">\u57fa\u76f8\u540c\u8207\u5f8c\u8a5e\u57fa\u76f8\u540c\u7684\u76f8\u4f3c\u8a5e\u70ba\u8a08\u7b97\u6a19\u7684\u3002\u5c0b\u627e\u5230\u524d\u8a5e\u57fa\u76f8\u540c\u8207\u5f8c\u8a5e\u57fa\u76f8\u540c\u7684\u76f8</td></tr><tr><td colspan=\"3\">\u4f3c\u8a5e\u5f8c\uff0c\u7b2c\u3193\u6b65\u9700\u8a08\u7b97\u9019\u4e9b\u9078\u53d6\u51fa\u4f86\u7684\u76f8\u4f3c\u8a5e\u3197\u8207\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u8a5e\u57fa\u76f8\u7570\u7684\u90e8\u5206</td></tr><tr><td colspan=\"3\">\u53ef\u6b78\u7d0d\u51fa\u53f3\u908a\u7684\u3194\u689d\u898f\u5247\uff0c\u898f\u5247\u4e4b\u524d\u7684\u6578\u91cf\u8868\u793a\u898f\u5247\u51fa\u73fe\u7684\u6b21\u6578\u3002\u3198\u5716\u70ba\u3197 \u7684\u76f8\u4f3c\u5ea6\u3002\u8a08\u7b97\u5169\u500b\u8a5e\u5f59\u76f8\u4f3c\u5ea6\u7684\u65b9\u6cd5\uff0c\u5982\u3198\uff1b</td></tr><tr><td>\u7814\u9662\u3197\u6587\u53e5\u7d50\u69cb\u6a39\u7684\u7bc4\u4f8b\uff1a</td><td/><td/></tr><tr><td>Sim(Word unknown ,Word known )</td><td/><td/></tr><tr><td>=w 1 *Score 1 +w 2 *Score 2</td><td/><td/></tr><tr><td colspan=\"3\">S VH \u985e\u8207 VA \u985e\u540c\u5c6c\u4e0d\u53ca\u7269\u52d5\u8a5e\uff0c\u4ed6\u5011\u7684\u5dee\u5225\u50c5\u5728\u65bc\u52d5\u4f5c\u8207\u72c0\u614b\u7684\u5340\u5206\u3002 =w 1 *HowNetSimScore(Base i ,Base j )</td></tr><tr><td colspan=\"3\">\u8868\u683c 1 \u8a5e\u985e\u76f8\u4f3c\u5ea6(\u90e8\u5206) +w 2 *CategoryScore(category(Base i ),category(Base j ))</td></tr><tr><td colspan=\"3\">\u8a5e\u985e 1 Word known \u70ba\u76f8\u4f3c\u8a5e theme NP quantity NP VH Base i \u70ba\u672a\u77e5\u52d5\u8a5e\u8207\u76f8\u4f3c\u8a5e\u76f8\u7570\u7684\u8a5e\u57fa \u8a5e\u985e 2 VA 1 quantity NP --&gt; Head_Neqa \u76f8\u4f3c\u5ea6 0.674 1 theme NP --&gt; head_Nad VH VC 0.611 Base j \u70ba\u76f8\u4f3c\u8a5e\u8207\u672a\u77e5\u52d5\u8a5e\u76f8\u7570\u7684\u8a5e\u57fa</td></tr><tr><td colspan=\"3\">VH VH \u6700\u5f8c\u3192\u500b\u6b65\u9a5f\u662f\u6c7a\u5b9a\u672a\u77e5\u52d5\u8a5e\u7684\u8a5e\u985e\u3002\u6211\u5011\u5df2\u6709\u4e86\u3192\u7fa4\u76f8\u4f3c\u8a5e\uff0c\u540c\u6642\u6bcf\u500b\u76f8\u4f3c\u8a5e VD 0.643 1 S --&gt; quantity_NP theme_NP Head_VH11 Head VH11 Head VE 0.540 Head Neqa Nad VH VG 0.591 \u4e5f\u6709\u8207\u672a\u77e5\u52d5\u8a5e\u7684\u76f8\u4f3c\u5206\u6578\u3002\u5148\u5c07\u9019\u4e9b\u76f8\u4f3c\u8a5e\u4f9d\u7167\u8a5e\u985e\u5206\u7d44\uff0c\u5f9e\u6bcf\u500b\u8a5e\u985e\u7576\u3197\u53d6</td></tr><tr><td colspan=\"3\">VH \u51fa K \u500b\u76f8\u4f3c\u8a5e\u51fa\u4f86\uff0c\u5c07\u9019\u4e9b\u76f8\u4f3c\u8a5e\u7684\u5206\u6578\u4e88\u4ee5\u5e73\u5747\uff0c\u5f97\u5230\u672a\u77e5\u52d5\u8a5e\u5230\u6bcf\u500b\u8a5e\u985e VH 1.000</td></tr><tr><td colspan=\"3\">VH \u7684\u5e73\u5747\u8ddd\u96e2\uff0c\u672a\u77e5\u52d5\u8a5e\u7684\u8a5e\u985e\u5373\u8207\u5176\u8ddd\u96e2\u6700\u76f8\u8fd1\u7684\u8a5e\u985e\u3002\u6211\u5011\u5c07\u5728\u3198\u3192\u7bc0\u6e2c\u8a66\u8a9e VI 0.736</td></tr><tr><td colspan=\"3\">Word1 \u610f\u76f8\u4f3c\u5ea6\u3197\u7684\u6bd4\u91cd\u3001\u8a9e\u610f\u8207\u8a5e\u985e\u7684\u6bd4\u91cd\u4ee5\u53ca K \u503c\u7684\u5927\u5c0f\u5c0d\u6b63\u78ba\u7387\u7684\u5f71\u97ff\u3002 Word2 VH VHC 0.852 Word3 VH VJ 0.655</td></tr><tr><td>\u5716 1 \u3197\u6587\u53e5\u7d50\u69cb\u6a39\u6a39\u72c0\u5716\u8207\u6b78\u7d0d\u898f\u5247 3. \u5be6\u9a57\u7d50\u679c</td><td/><td/></tr><tr><td>2-3 \u76f8\u4f3c\u8a5e\u7684\u9078\u53d6</td><td/><td/></tr><tr><td colspan=\"3\">\u6bcf\u3192\u500b\u8a5e\u985e\u7684\u5411\u91cf\u7531\u5404\u7236\u7bc0\u9ede\u8207\u5144\u7bc0\u9ede\u51fa\u73fe\u7684\u983b\u7387\u7d44\u6210\uff0c\u5148\u70ba\u653e\u5165\u5404\u7236\u7bc0\u9ede\u7684\u983b \u5728\u4f7f\u7528\u76f8\u4f3c\u6cd5\u4f86\u9810\u6e2c\u52d5\u8a5e\u5206\u985e\u7684\u904e\u7a0b\u3197\uff0c\u3194\u500b\u4e3b\u8981\u7684\u6b65\u9a5f\u3002\u3192\u70ba\u672a\u77e5\u52d5\u8a5e\u7684 \u7387\uff0c\u518d\u4f9d\u6b21\u653e\u5165\u5144\u7bc0\u9ede\u7684\u983b\u7387\uff0c\u82e5\u8a72\u500b\u7bc0\u9ede\u6c92\u51fa\u73fe\u5728\u8a72\u8a5e\u985e\u3197\uff0c\u5247\u653e\u5165\u70ba 0\u3002\u5b9a \u76f8\u4f3c\u8a5e\u7684\u9078\u53d6\uff0c\u3193\u70ba\u6e2c\u91cf\u672a\u77e5\u52d5\u8a5e\u8207\u76f8\u4f3c\u8a5e\u7684\u76f8\u4f3c\u5ea6\uff0c\u3194\u70ba\u6c7a\u5b9a\u672a\u77e5\u52d5\u8a5e\u7684\u8a5e\u985e\u3002 \u7fa9\u5982\u3198\uff1a \u9996\u5148\uff0c\u7576\u3192\u500b\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u51fa\u73fe\u6642\uff0c\u6211\u5011\u4e26\u4e0d\u77e5\u9053\u54ea\u4e9b\u8a13\u7df4\u8a9e\u6599\u7684\u52d5\u8a5e\u8207\u65b0</td></tr><tr><td colspan=\"3\">Set)\uff0c\u6e2c\u8a66\u8a9e\u6599\u7684\u6b63\u78ba\u7b54\u6848\u70ba\u319f\u5de5\u6a19\u8a18\u7684\u8a5e\u985e\u3002 \u7684\u672a\u77e5\u52d5\u8a5e\u8f03\u76f8\u4f3c\uff0c\u56e0\u6b64\u7406\u8ad6\u3196\u6211\u5011\u5fc5\u9808\u8a08\u7b97\u6bcf\u500b\u8a13\u7df4\u8a9e\u6599\u3197\u7684\u52d5\u8a5e\u8207\u65b0\u7684\u672a\u77e5 i={VA, VAC, VB, VC, VCL,\u2026Na, Nb\u2026.A,\u2026P,\u2026} \u52d5\u8a5e\u7684\u76f8\u4f3c\u5ea6\uff0c\u5c0b\u627e\u51fa\u76f8\u4f3c\u5ea6\u8f03\u9ad8\u7684\u76f8\u4f3c\u8a5e\u4f5c\u70ba\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u9810\u6e2c\u8a5e\u985e\u7684\u4f9d\u64da\uff0c \u5728\u76f8\u4f3c\u6cd5\u3197\u9700\u8981\u8a0e\u8ad6\u3198\u5217\u3194\u9ede\u3002\u3192\u3001\u8abf\u6574\u8a9e\u610f\u76f8\u4f3c\u5ea6\u3197\u7684\u4e3b\u8981\u7fa9\u539f\u8207\u6b21\u8981\u7fa9</td></tr><tr><td colspan=\"3\">=&lt; \u8a08\u7b97\u65b0\u7684\u672a\u77e5\u52d5\u8a5e\u8207\u8a13\u7df4\u8a9e\u6599\u3197\u52d5\u8a5e\u7684\u5b9a\u7fa9\u5982\u3198\uff1a ),...freq( node t freq(paren ), node t freq(paren Category 2 1 i \u539f\u9593\u7684\u6bd4\u91cd\uff0c\u3193\u3001\u8abf\u6574\u8a9e\u610f\u8207\u8a5e\u985e\u5169\u7a2e\u76f8\u4f3c\u5ea6\u7684\u6bd4\u91cd\uff0c\u3194\u3001\u8abf\u6574 K \u503c\u7684\u5927\u5c0f\uff0c node (sibling freq ), node parent n</td><td>1</td><td>),</td></tr><tr><td>node \u4f7f\u6574\u500b\u7cfb\u7d71\u7684\u6b63\u78ba\u7387\u9054\u5230\u6700\u4f73\u72c0\u614b\u3002 ng freq(sibli ),..., node ng freq(sibli m 2</td><td>)</td><td>&gt;</td></tr><tr><td colspan=\"3\">If Word= wordbase 1 +wordbase 2 +wordbase 3 ...+wordbase n</td></tr><tr><td colspan=\"3\">\u6b63\u78ba\u7387\u7684\u5b9a\u7fa9\u70ba\uff1a Sim(Word unknown ,Word known ) \u5f97\u5230\u5404\u500b\u8a5e\u985e\u7684\u5411\u91cf\u5f8c\uff0c\u6211\u5011\u5229\u7528\u3198\u5217\u516c\u5f0f\u8a08\u7b97\u8a5e\u985e\u8207\u8a5e\u985e\u4e4b\u9593\u7684\u76f8\u4f3c\u7a0b\u5ea6\uff0c\u6240 \u5f97\u7684\u5206\u6578\u4ecb\u65bc 0~1 \u4e4b\u9593\uff0c1 \u8868\u793a\u5b8c\u5168\u76f8\u540c\uff0c0 \u8868\u793a\u5b8c\u5168\u4e0d\u76f8\u540c\u3002 =weight 1 *Sim(wordbase 1-unknown ,wordbase 1-known ) \u6b63\u78ba\u7387\uff1d\u731c\u6e2c\u6b63\u78ba\u7684\u672a\u77e5\u52d5\u8a5e/(1000-\u7121\u6cd5\u731c\u6e2c\u7684\u672a\u77e5\u52d5\u8a5e)</td></tr><tr><td colspan=\"3\">+weight 2 *Sim(wordbase 2-unknown ,wordbase 2-known )</td></tr><tr><td>+...</td><td/><td/></tr><tr><td colspan=\"3\">+weight n *Sim(wordbase n-unknown ,wordbase n-known )</td></tr></table>",
"text": "\u6211\u5011\u5217\u51fa\u90e8\u5206 VH \u985e\u7684\u52d5\u8a5e\u8207\u5404\u985e\u52d5\u8a5e\u7684\u76f8\u4f3c\u5ea6\u65bc\u8868\u683c 1\u3002\u9664\u4e86 VH \u985e\u3198\u7684\u5206\u985e VHC \u985e\u5916\uff0cVH \u985e\u52d5\u8a5e\u8207 VI \u985e\u76f8\u4f3c\u7a0b\u5ea6\u6700\u9ad8\uff0cVH \u985e\u8207 VI \u985e\u5169\u8005\u7686\u70ba\u72c0\u614b\u52d5\u8a5e\uff0c \u4ed6\u5011\u7684\u5dee\u5225\u50c5\u5728\u65bc\u53ef\u63a5\u7684\u8ad6\u5143\u6578\u91cf\u3002VI \u985e\u70ba\u985e\u55ae\u8cd3\u52d5\u8a5e\uff0c\u57fa\u672c\u3196\u4e5f\u662f\u4e0d\u53ca\u7269\u52d5 \u8a5e\uff0c\u4f46\u662f VI \u985e\u7684\u52d5\u8a5e\u5728\u8a9e\u610f\u3196\u53ef\u63a5\u53d7\u3192\u500b\u8ad6\u5143\uff0c\u4f46\u8a72\u8ad6\u5143\u7684\u4f4d\u7f6e\u4e0d\u51fa\u73fe\u5728\u52d5\u8a5e \u4e4b\u5f8c\uff0c\u901a\u5e38\u4f7f\u7528\u3192\u500b\u4ecb\u8a5e\u5c07\u8ad6\u5143\u5f15\u4ecb\u51fa\u4f86\u3002\u800c VH \u985e\u8207 VA \u985e\u7684\u76f8\u4f3c\u7a0b\u5ea6\u70ba\u6b21\u9ad8\uff0c",
"num": null,
"html": null
}
}
}
}