id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
SCOPUS_ID:85146435072 | A Hybrid Semantic Statistical Query Expansion for Arabic Information Retrieval Systems | Query-document vocabulary mismatch, the lack of query expressiveness for user needs and the phenomenon of short queries are the main issues associated with information retrieval systems. Query Expansion (QE) is one of the well-known alternative for overcoming these problems. It mainly involves finding synonyms or relat... | [
"Semantic Text Processing",
"Information Retrieval",
"Representation Learning"
] | [
72,
24,
12
] |
SCOPUS_ID:85130365626 | A Hybrid Semantic-Topic Co-encoding Network for Social Emotion Classification | Social emotion classification is to predict the distribution of readers’ emotions evoked by a document (e.g., news article). Previous work has shown that both semantic and topical information can help improve classification performance. However, many existing topic-based neural models represent the topical feature of d... | [
"Text Classification",
"Sentiment Analysis",
"Emotion Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
78,
61,
24,
3
] |
SCOPUS_ID:85093090755 | A Hybrid Sentiment Analysis Method | Sentiment analysis has attracted a wide range of attentions in the last few years. Supervised-based and lexicon-based methods are two mainly sentiment analysis categories. Supervised-based approaches could get excellent performance with sufficient tagged samples, while the acquisition of sufficient tagged samples is di... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Sentiment Analysis"
] | [
3,
24,
36,
78
] |
SCOPUS_ID:84946555797 | A Hybrid Sentiment Lexicon for Social Media Mining | Sentiment lexicon is a crucial resource for opinion mining from social media content. However, standard off-the-shelve lexicons are static and typically do not adapt, in content and context, to a target domain. This limitation, adversely affects the effectiveness of sentiment analysis algorithms. In this paper, we intr... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85101743197 | A Hybrid Sequential Model for Text Simplification | Learning different subjects to enhance knowledge of students and children, reading habit plays an important role. Students often face problems or reading difficulties are aroused when the students are non-native English learners or suffering from dyslexia. Thus, in the present work, we have built a hybrid sequential mo... | [
"Language Models",
"Paraphrasing",
"Machine Translation",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Named Entity Recognition",
"Text Generation",
"Multilinguality"
] | [
52,
32,
51,
72,
3,
34,
47,
0
] |
SCOPUS_ID:85114284006 | A Hybrid Siamese Neural Network for Natural Language Inference in Cyber-Physical Systems | Cyber-Physical Systems (CPS), as a multi-dimensional complex system that connects the physical world and the cyber world, has a strong demand for processing large amounts of heterogeneous data. These tasks also include Natural Language Inference (NLI) tasks based on text from different sources. However, the current res... | [
"Reasoning",
"Textual Inference"
] | [
8,
22
] |
SCOPUS_ID:85122575847 | A Hybrid Similarity Measure for Dynamic Service Discovery and Composition based on Mobile Agents | With the ever-present competition among companies, the prevalence of web services (WSs) is increasing dramatically. This leads to the diversity of the similar services and their developed nature, which makes the discovery of a relevant service during the composition phase a complex task. Since most of the competition c... | [
"Semantic Text Processing",
"Semantic Similarity"
] | [
72,
53
] |
SCOPUS_ID:85078503038 | A Hybrid Social Mining Approach for Companies Current Reputation Analysis | This paper presents an approach for company’s reputation analysis using data mining techniques. It obtains knowledge from huge data written about these companies and available publicly on the internet. It is done by extracting data from social media, such as twitter, containing relevant company’s mentions. Then, data i... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:84978056076 | A Hybrid Strategy for Chinese Domain-Specific Terminology Extraction | Automatic Term Extraction is an important issue in Natural Language Processing. This paper presents a new approach of terminology extraction combining with machine learning based on cascaded conditional random fields and corpus-based statistical model. In this approach, firstly, the low-layer and high-layer conditional... | [
"Term Extraction",
"Information Extraction & Text Mining"
] | [
1,
3
] |
SCOPUS_ID:85116495348 | A Hybrid Supervised/Unsupervised Machine Learning Approach to Classify Web Services | Reusing software is a promising way to reduce software development costs. Nowadays, applications compose available web services to build new software products. In this context, service composition faces the challenge of proper service selection. This paper presents a model for classifying web services. The service data... | [
"Low-Resource NLP",
"Information Extraction & Text Mining",
"Text Classification",
"Text Clustering",
"Information Retrieval",
"Responsible & Trustworthy NLP"
] | [
80,
3,
36,
29,
24,
4
] |
SCOPUS_ID:85067393016 | A Hybrid System for Chinese Grammatical Error Diagnosis and Correction | This paper introduces the DM NLP team's system for NLPTEA 2018 shared task of Chinese Grammatical Error Diagnosis (CGED), which can be used to detect and correct grammatical errors in texts written by Chinese as a Foreign Language (CFL) learners. This task aims at not only detecting four types of grammatical errors inc... | [
"Text Error Correction",
"Syntactic Text Processing"
] | [
26,
15
] |
https://aclanthology.org//2020.nlptea-1.9/ | A Hybrid System for NLPTEA-2020 CGED Shared Task | This paper introduces our system at NLPTEA2020 shared task for CGED, which is able to detect, locate, identify and correct grammatical errors in Chinese writings. The system consists of three components: GED, GEC, and post processing. GED is an ensemble of multiple BERT-based sequence labeling models for handling GED t... | [
"Text Error Correction",
"Syntactic Text Processing"
] | [
26,
15
] |
http://arxiv.org/abs/2102.04506v1 | A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining | This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9). Participants in the shared task build an end-to-end task completion dialog system which is evaluated by human evaluation and a user simulator based automatic eva... | [
"Language Models",
"Natural Language Interfaces",
"Semantic Text Processing",
"Dialogue Systems & Conversational Agents"
] | [
52,
11,
72,
38
] |
SCOPUS_ID:85141710090 | A Hybrid Translation Model for Pidgin English to English Language Translation | The African continent is made up of people with rich diverse cultures and spoken languages. Despite the diversity, one common point of unification, especially among the West African communities is the spoken pidgin-English language. With the development in web technology and the English language dominancy of web conten... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:85143058204 | A Hybrid Video-to-Text Summarization Framework and Algorithm on Cascading Advanced Extractiveand Abstractive-based Approaches for Supporting Viewers' Video Navigation and Understanding | In this work, we propose the development of a hybrid video-to-text summarization (VTS) framework on cascading the advanced and code-accessible extractive and abstractive (EA) approaches for supporting viewers' video navigation and understanding. More precisely, the contributions of this paper are three-fold. First, we ... | [
"Visual Data in NLP",
"Information Extraction & Text Mining",
"Captioning",
"Summarization",
"Text Generation",
"Multimodality"
] | [
20,
3,
39,
30,
47,
74
] |
http://arxiv.org/abs/1802.09968v2 | A Hybrid Word-Character Approach to Abstractive Summarization | Automatic abstractive text summarization is an important and challenging research topic of natural language processing. Among many widely used languages, the Chinese language has a special property that a Chinese character contains rich information comparable to a word. Existing Chinese text summarization methods, eith... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85075244038 | A Hybrid and Adaptive Approach for Classification of Indian Stock Market-Related Tweets | Twitter generates an enormous amount of data daily. Various studies over the years have concluded that tweets have a significant impact in predicting and understanding the stock price movement. Designing a system to store relevant tweets and extracting information for specific stocks and industry is a relevant and unat... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85101962545 | A Hybrid and Explainable Deep Learning Framework for SAR Images | Deep learning based patch-wise Synthetic Aperture Radar (SAR) image classification usually requires a large number of labeled data for training. Aiming at understanding SAR images with very limited annotation and taking full advantage of complex-valued SAR data, this paper proposes a general and practical framework for... | [
"Visual Data in NLP",
"Topic Modeling",
"Explainability & Interpretability in NLP",
"Multimodality",
"Responsible & Trustworthy NLP",
"Information Extraction & Text Mining"
] | [
20,
9,
81,
74,
4,
3
] |
SCOPUS_ID:84970950210 | A Hybrid method of analyzing patents for sustainable technology management in humanoid robot industry | A humanoid, which refers to a robot that resembles a human body, imitates a human's intelligence, behavior, sense, and interaction in order to provide various types of services to human beings. Humanoids have been studied and developed constantly in order to improve their performance. Humanoids were previously develope... | [
"Responsible & Trustworthy NLP",
"Topic Modeling",
"Information Extraction & Text Mining",
"Green & Sustainable NLP"
] | [
4,
9,
3,
68
] |
SCOPUS_ID:85125187669 | A Hybrid of Rule-based and HMM-based Part-of-Speech Tagger for Indonesian | Aksara is an Indonesian NLP tool that conforms to Universal Dependencies annotation guidelines. So far, Aksara can perform four tasks: word segmentation, lemmatization, POS tagging, and morphological features analysis. However, one of its weaknesses is that it has not solved the word sense disambiguation problem. This ... | [
"Tagging",
"Syntactic Text Processing"
] | [
63,
15
] |
SCOPUS_ID:85102083087 | A Hybridized Deep Learning Method for Bengali Image Captioning | An omnipresent challenging research topic in computer vision is the generation of captions from an input image. Previously, numerous experiments have been conducted on image captioning in English but the generation of the caption from the image in Bengali is still sparse and in need of more refining. Only a few papers ... | [
"Visual Data in NLP",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
39,
47,
74
] |
SCOPUS_ID:85107338758 | A Hyperintensional Theory of Intelligent Question Answering in TIL | The paper deals with natural language processing and question answering over large corpora of formalised natural language texts. Our background theory is the system of Transparent Intensional Logic (TIL) which is a partial, hyperintensional, typed λ -calculus. Having a fine-grained analysis of natural language sentence... | [
"Linguistic Theories",
"Question Answering",
"Natural Language Interfaces",
"Linguistics & Cognitive NLP",
"Reasoning"
] | [
57,
27,
11,
48,
8
] |
SCOPUS_ID:78649575005 | A Hyperlipemia Information Analysis System based on immune algorithm | This paper designs a Hyperlipemia Information Analysis System, which can realize hyperlipemia document classification and information analysis. In document indexing, we propose an improved approach, called Term Frequency, Inverted Document Frequency and Inverted Entropy (TFIDFIE), to compute term weights in document in... | [
"Indexing",
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
69,
24,
36,
3
] |
SCOPUS_ID:80052246594 | A Hypothesis About the Biological Basis of Expert Intuition | It is well established that intuition plays an important role in experts' decision making and thinking generally. However, the theories that have been developed at the cognitive level have limits in their explanatory power and lack detailed explanation of the underlying biological mechanisms. In this paper, we bridge t... | [
"Chunking",
"Syntactic Text Processing",
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
43,
15,
48,
57
] |
SCOPUS_ID:84937046300 | A Iacopone's anthology. The Tresatti collection | In 1617, the Franciscan monk Francesco Tresatti da Lugnano produced an extensive annotated edition of Le poesie spirituali del B. Iacopone da Todi for Nicolò Misserini's printing house in Venice. This article reveals the limitations which emerge from the questionable methods of textual criticism adopted by the... | [
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
48,
57
] |
SCOPUS_ID:85065412446 | A Information Retrieval Based on Question and Answering and NER for Unstructured Information Without Using SQL | In today’s world, the availability of information in the form of unstructured data is in abundance. The unstructured information received is more often than not in the form of natural language text. For any defense establishment, the spy data or any sensitive information received may be best utilized when the informati... | [
"Programming Languages in NLP",
"Structured Data in NLP",
"Question Answering",
"Named Entity Recognition",
"Multimodality",
"Natural Language Interfaces",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
55,
50,
27,
34,
74,
11,
24,
3
] |
SCOPUS_ID:85101724948 | A Intelligent CNN-BiLSTM Approach for Chinese Sentiment Analysis on Spark | Short text Chinese sentiment classification has become an important task in sentiment analysis fields. In recent years, deep learning-based methods have been widely used in sentiment classification. However, with the complexity of deep learning models, the number of model parameters has increased. The effectiveness of ... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
78,
24,
3
] |
SCOPUS_ID:0342725926 | A JAPANESE TEXT-TO-SPEECH SYSTEM BASED ON MULTI-FORM UNITS WITH CONSIDERATION OF FREQUENCY DISTRIBUTION IN JAPANESE | This paper proposes our new text-to-speech (TTS) system that concatenates large numbers of speech segments to produce very natural and intelligible synthetic speech. One novel point of our system is its new synthesis unit, which is has three remarkable characteristics as follows; (1) The synthesis units contain all Jap... | [
"Speech & Audio in NLP",
"Multimodality"
] | [
70,
74
] |
SCOPUS_ID:0034229902 | A JPEG variable quantization method for compound documents | In this paper, we present a JPEG-compliant method for the efficient compression of compound documents using variable quantization. Based on the DCT activity of each 8 x 8 block, our scheme automatically adjusts the quantization scaling factors so that text blocks are compressed at higher quality than image blocks. Resu... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85126259121 | A Japanese 4-year-old with protracted phonological development: the challenge of coronals | This study examines the phonology of a Japanese four-year-old with mildly protracted phonological development (PPD) as a contribution to a special crosslinguistic issue presenting individual profiles in PPD within the framework of constraint-based nonlinear phonology. Although the child’s word structure and vowels were... | [
"Phonology",
"Syntactic Text Processing"
] | [
6,
15
] |
https://aclanthology.org//W09-0618/ | A Japanese Corpus of Referring Expressions Used in a Situated Collaboration Task | [
"Text Generation"
] | [
47
] | |
SCOPUS_ID:85141884336 | A Japanese Dataset for Subjective and Objective Sentiment Polarity Classification in Micro Blog Domain | We annotate 35,000 SNS posts with both the writer's subjective sentiment polarity labels and the reader's objective ones to construct a Japanese sentiment analysis dataset. Our dataset includes intensity labels (none, weak, medium, and strong) for each of the eight basic emotions by Plutchik (joy, sadness, anticipation... | [
"Text Classification",
"Polarity Analysis",
"Sentiment Analysis",
"Emotion Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
33,
78,
61,
24,
3
] |
SCOPUS_ID:84885462223 | A Japanese OCR post-processing approach based on dictionary matching | This paper describes a post-processing approach for Japanese character recognition based on dictionary. By the analysis of experimental data in the processing of OCR, we find that some segmentation and recognition results do not conform to the rules of lexical and just generate the character based on the shape. If the ... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
https://aclanthology.org//W02-1114/ | A Japanese Semantic Network Built on a Pulsed Neural Network with Encoding Associative Concept Dictionaries | [
"Knowledge Representation",
"Semantic Text Processing"
] | [
18,
72
] | |
SCOPUS_ID:57849165426 | A Japanese language model with quote detection by using surface information | In natural language processing, quotes are an important grammatical category which needs consideration. In this paper, we propose a Japanese language model that includes quotes as a category. The quotes are recognized by using surface information and dependencies between the words. Then, they are divided into direct an... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
https://aclanthology.org//2007.mtsummit-papers.63/ | A Japanese-English patent parallel corpus | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] | |
SCOPUS_ID:79959912368 | A Java implementation of a Question Answering System based on conditional knowledge in client-server technology | A conditional schema is a graph-based structure which is able to represent conditional knowledge. This structure was introduced in [1]. The inference mechanism corresponding to the conditional schema representations was developed in [2]. A Question Answering System based on conditional knowledge was presented in [3]. I... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
SCOPUS_ID:85062808373 | A Javanese Syllabifier Based on its Orthographic System | Automatic syllabification is considered as a finished process in high-resource languages. However, it is still badly needed in under-resourced and critical languages such as Javanese. Syllabification becomes the basic backbone in any task related to transliteration process for Abugida or syllabary scripts, word recogni... | [
"Text Segmentation",
"Syntactic Text Processing"
] | [
21,
15
] |
SCOPUS_ID:85125350735 | A Joint Entity-Relation Extraction Method with Sparse Parameter Sharing Architecture | The existing parameter sharing joint entity-relation extraction models cannot learn task-specific features for named entity recognition and relation classification subtasks. To address the problem, this work proposed a sparse parameter sharing joint entity-relation extraction method. The proposed method incorporates a ... | [
"Relation Extraction",
"Information Extraction & Text Mining"
] | [
75,
3
] |
SCOPUS_ID:85137176909 | A Joint Extraction Strategy for Chinese Medical Text Based on Sequence Tagging | The research on entities and relations extraction in medical text is the basis of constructing medical knowledge graphs. Currently the mainstream pipelined extraction method do not consider the connection between entity recognition and relation classification, and could not address the problem of the overlapping relati... | [
"Language Models",
"Semantic Text Processing",
"Syntactic Text Processing",
"Representation Learning",
"Tagging",
"Information Extraction & Text Mining"
] | [
52,
72,
15,
12,
63,
3
] |
SCOPUS_ID:85128929881 | A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation | With the development of recommendation systems (RSs), researchers are no longer only satisfied with the recommendation results, but also put forward requirements for the recommendation reasons, which helps improve user experience and discover system defects. Recently, some methods develop knowledge graph reasoning via ... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Representation Learning",
"Explainability & Interpretability in NLP",
"Knowledge Representation",
"Knowledge Graph Reasoning",
"Responsible & Trustworthy NLP",
"Reasoning",
"Multimodality"
] | [
72,
50,
12,
81,
18,
54,
4,
8,
74
] |
SCOPUS_ID:85145349140 | A Joint Knowledge Graph Reasoning Method | Facing the massive data generated by edge intelligent interconnection applications in the mobile edge computing (MEC) environment, timely and efficient data mining has become an urgent technical problem to be solved. Knowledge graph reasoning is a promising solution to the above challenges. However, the traditional kno... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Knowledge Representation",
"Knowledge Graph Reasoning",
"Reasoning",
"Multimodality"
] | [
72,
50,
18,
54,
8,
74
] |
SCOPUS_ID:85140453672 | A Joint Label-Enhanced Representation Based on Pre-trained Model for Charge Prediction | As one of the important subtasks of legal judgment prediction, charge prediction aims to predict the final charge according to the fact description of a legal case. It can help make legal judgments or provide legal professional guidance for non-professionals. Most existing works focus on predicting charges only based o... | [
"Low-Resource NLP",
"Language Models",
"Semantic Text Processing",
"Representation Learning",
"Responsible & Trustworthy NLP"
] | [
80,
52,
72,
12,
4
] |
http://arxiv.org/abs/2010.11980v1 | A Joint Learning Approach based on Self-Distillation for Keyphrase Extraction from Scientific Documents | Keyphrase extraction is the task of extracting a small set of phrases that best describe a document. Most existing benchmark datasets for the task typically have limited numbers of annotated documents, making it challenging to train increasingly complex neural networks. In contrast, digital libraries store millions of ... | [
"Language Models",
"Information Extraction & Text Mining",
"Semantic Text Processing",
"Green & Sustainable NLP",
"Term Extraction",
"Responsible & Trustworthy NLP"
] | [
52,
3,
72,
68,
1,
4
] |
http://arxiv.org/abs/2204.03208v1 | A Joint Learning Approach for Semi-supervised Neural Topic Modeling | Topic models are some of the most popular ways to represent textual data in an interpret-able manner. Recently, advances in deep generative models, specifically auto-encoding variational Bayes (AEVB), have led to the introduction of unsupervised neural topic models, which leverage deep generative models as opposed to t... | [
"Low-Resource NLP",
"Topic Modeling",
"Information Retrieval",
"Responsible & Trustworthy NLP",
"Text Classification",
"Information Extraction & Text Mining"
] | [
80,
9,
24,
4,
36,
3
] |
SCOPUS_ID:85128855720 | A Joint Learning Method for Biomedical Entity Linking | Biomedical texts contain valuable domain knowledge for biomedical researchers. It is of great significance to make full use of massive biomedical literature, discover important hidden information and acquire professional knowledge from it. Biomedical entity linking is the identification of a named entity in a biomedica... | [
"Knowledge Representation",
"Named Entity Recognition",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
18,
34,
72,
3
] |
SCOPUS_ID:85133264484 | A Joint Learning Model to Extract Entities and Relations for Chinese Literature Based on Self-Attention | Extracting structured information from massive and heterogeneous text is a hot research topic in the field of natural language processing. It includes two key technologies: named entity recognition (NER) and relation extraction (RE). However, previous NER models consider less about the influence of mutual attention bet... | [
"Language Models",
"Semantic Text Processing",
"Relation Extraction",
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
52,
72,
75,
34,
3
] |
SCOPUS_ID:85147673109 | A Joint Learning Sentiment Analysis Method Incorporating Emoji-Augmentation | Social media is the platform for most people to share their opinions, emojis are also widely used to express moods, emotions, and feelings on social media. There have been many researched on emojis and sentiment analysis. However, existing methods mainly face two limitations. First, since deep learning relies on large ... | [
"Visual Data in NLP",
"Multimodality",
"Sentiment Analysis"
] | [
20,
74,
78
] |
SCOPUS_ID:85063904782 | A Joint Model based on CNN-LSTMs in Dialogue Understanding | In Task-oriented Dialogue System, intent recognition and slot filling are two key subtasks of dialogue understanding (DU) module. Considering the strong relationship between intent and slots, this paper proposes an encoder-decoder architecture (using CNN-LSTMs) which based on attention mechanism to jointly model the tw... | [
"Language Models",
"Semantic Text Processing",
"Semantic Parsing",
"Sentiment Analysis",
"Intent Recognition",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
52,
72,
40,
78,
79,
11,
38
] |
SCOPUS_ID:85097309159 | A Joint Model for Aspect-Category Sentiment Analysis with Shared Sentiment Prediction Layer | Aspect-category sentiment analysis (ACSA) aims to predict the aspect categories mentioned in texts and their corresponding sentiment polarities. Some joint models have been proposed to address this task. Given a text, these joint models detect all the aspect categories mentioned in the text and predict the sentiment po... | [
"Aspect-based Sentiment Analysis",
"Sentiment Analysis"
] | [
23,
78
] |
http://arxiv.org/abs/1911.01678v4 | A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency | Definition Extraction (DE) is one of the well-known topics in Information Extraction that aims to identify terms and their corresponding definitions in unstructured texts. This task can be formalized either as a sentence classification task (i.e., containing term-definition pairs or not) or a sequential labeling task (... | [
"Syntactic Text Processing",
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
15,
24,
36,
3
] |
http://arxiv.org/abs/2106.03345v1 | A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech | In this paper, we present a neural model for joint dropped pronoun recovery (DPR) and conversational discourse parsing (CDP) in Chinese conversational speech. We show that DPR and CDP are closely related, and a joint model benefits both tasks. We refer to our model as DiscProReco, and it first encodes the tokens in eac... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Semantic Parsing",
"Speech & Audio in NLP",
"Discourse & Pragmatics",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Multimodality"
] | [
72,
50,
40,
70,
71,
11,
38,
74
] |
SCOPUS_ID:85129664788 | A Joint Model for Extracting Latent Aspects and Their Ratings From Online Employee Reviews | The personal description of a company associated with job satisfaction, company culture, and opinions of senior leadership is available on workplace community websites. However, it is almost impossible to read all of the different and possibly even contradictory reviews and make an accurate overall rating. Therefore, e... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85097264282 | A Joint Model for Graph-Based Chinese Dependency Parsing | In Chinese dependency parsing, the joint model of word segmentation, POS tagging and dependency parsing has become the mainstream framework because it can eliminate error propagation and share knowledge, where the transition-based model with feature templates maintains the best performance. Recently, the graph-based jo... | [
"Structured Data in NLP",
"Syntactic Text Processing",
"Syntactic Parsing",
"Tagging",
"Text Segmentation",
"Multimodality"
] | [
50,
15,
28,
63,
21,
74
] |
SCOPUS_ID:85130800236 | A Joint Model for Hierarchical Nested Information Extraction | During the long-term power construction process, the power dispatching department has saved many notification texts related to adjustment of grid operation mode. There is an urgent need to study named entity recognition techniques to automatically recognize the power equipment and operation mode, in order to support au... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
http://arxiv.org/abs/1901.01010v2 | A Joint Model for Multimodal Document Quality Assessment | The quality of a document is affected by various factors, including grammaticality, readability, stylistics, and expertise depth, making the task of document quality assessment a complex one. In this paper, we explore this task in the context of assessing the quality of Wikipedia articles and academic papers. Observing... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85103754875 | A Joint Model for Named Entity Recognition with Sentence-Level Entity Type Attentions | Named entity recognition (NER) is one fundamental task in natural language processing, which is typically addressed by neural condition random field (CRF) models, regarding the task as a sequence labeling problem. Sentence-level information has been shown positive for the task. Equipped with sophisticated neural struct... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
https://aclanthology.org//W09-4503/ | A Joint Model for Normalizing Gene and Organism Mentions in Text | [
"Information Extraction & Text Mining"
] | [
3
] | |
http://arxiv.org/abs/1706.01450v1 | A Joint Model for Question Answering and Question Generation | We propose a generative machine comprehension model that learns jointly to ask and answer questions based on documents. The proposed model uses a sequence-to-sequence framework that encodes the document and generates a question (answer) given an answer (question). Significant improvement in model performance is observe... | [
"Question Answering",
"Natural Language Interfaces",
"Question Generation",
"Text Generation"
] | [
27,
11,
76,
47
] |
SCOPUS_ID:84936930061 | A Joint Model for Topic-Sentiment Evolution over Time | Most existing topic models focus either on extracting static topic-sentiment conjunctions or topic-wise evolution over time leaving out topic-sentiment dynamics and missing the opportunity to provide a more in-depth analysis of textual data. In this paper, we propose an LDA-based topic model for analyzing topic-sentime... | [
"Topic Modeling",
"Information Extraction & Text Mining",
"Sentiment Analysis"
] | [
9,
3,
78
] |
https://aclanthology.org//W16-1603/ | A Joint Model for Word Embedding and Word Morphology | This paper presents a joint model for performing unsupervised morphological analysis on words, and learning a character-level composition function from morphemes to word embeddings. Our model splits individual words into segments, and weights each segment according to its ability to predict context words. Our morpholog... | [
"Representation Learning",
"Semantic Text Processing",
"Syntactic Text Processing",
"Morphology"
] | [
12,
72,
15,
73
] |
SCOPUS_ID:85085038971 | A Joint Model of Named Entity Recognition and Coreference Resolution Based on Hybrid Neural Network | Considering that both named entity recognition and coreference resolution depend on the same context of the entity word, this paper proposes a hybrid neural network model to settle these problems which contains a named entity recognition (NER) module and a coreference resolution (CR) module.NER and CR share a same bidi... | [
"Language Models",
"Semantic Text Processing",
"Named Entity Recognition",
"Coreference Resolution",
"Information Extraction & Text Mining"
] | [
52,
72,
34,
13,
3
] |
SCOPUS_ID:85060384403 | A Joint Model of Term Extraction and Polarity Classification for Aspect-based Sentiment Analysis | Aspect-based sentiment analysis (ABSA) is a significant task in opinion mining, which aims to extract explicit aspects of an entity along with the sentiment expressed towards these aspects. To achieve this goal, two subtasks are performed: aspect term extraction (ATE) and aspect polarity classification (APC). However, ... | [
"Information Retrieval",
"Opinion Mining",
"Term Extraction",
"Polarity Analysis",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
49,
1,
33,
23,
78,
36,
3
] |
SCOPUS_ID:85123445683 | A Joint Model with Multi-Granularity Features of Low-resource Language POS Tagging and Dependency Parsing | The study of part-of-speech tags and dependency parsing of low-resource languages plays an important role in promoting low-resource natural language processing tasks. For low-resource language word embedding representation, the existing work does not make full use of character and sub-word level information encoding, r... | [
"Low-Resource NLP",
"Semantic Text Processing",
"Syntactic Text Processing",
"Representation Learning",
"Syntactic Parsing",
"Tagging",
"Responsible & Trustworthy NLP"
] | [
80,
72,
15,
12,
28,
63,
4
] |
SCOPUS_ID:85054275888 | A Joint Multi-Task Learning Framework for Spoken Language Understanding | Spoken language understanding (SLU), which mainly involves intent prediction and slot filling, is a core component of a spoken dialogue system. Usually, intent determination and slot filling are carried out independently. Recently, joint learning of intent determination and slot filling has been proved effective in SLU... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Semantic Parsing",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
40,
11,
38,
4
] |
http://arxiv.org/abs/1411.5732v1 | A Joint Probabilistic Classification Model of Relevant and Irrelevant Sentences in Mathematical Word Problems | Estimating the difficulty level of math word problems is an important task for many educational applications. Identification of relevant and irrelevant sentences in math word problems is an important step for calculating the difficulty levels of such problems. This paper addresses a novel application of text categoriza... | [
"Text Classification",
"Reasoning",
"Numerical Reasoning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
8,
5,
24,
3
] |
SCOPUS_ID:84936797525 | A Joint Segmentation and Classification Framework for Sentence Level Sentiment Classification | In this paper, we propose a joint segmentation and classification framework for sentence-level sentiment classification. It is widely recognized that phrasal information is crucial for sentiment classification. However, existing sentiment classification algorithms typically split a sentence as a word sequence, which do... | [
"Information Retrieval",
"Syntactic Text Processing",
"Polarity Analysis",
"Sentiment Analysis",
"Text Segmentation",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
15,
33,
78,
21,
36,
3
] |
SCOPUS_ID:85106008006 | A Joint Sentiment-Topic Model for Product Review Analysis of Electronic Goods | Online product review plays an important role in raising the voice of customers and their purchase decision. However, a conventional method in the area has largely focused on field research and surveys to acquire information about customer preferences. The already existing frameworks largely focus on supervised learnin... | [
"Topic Modeling",
"Information Extraction & Text Mining",
"Sentiment Analysis"
] | [
9,
3,
78
] |
http://arxiv.org/abs/2101.00816v2 | A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis | Aspect based sentiment analysis (ABSA) involves three fundamental subtasks: aspect term extraction, opinion term extraction, and aspect-level sentiment classification. Early works only focused on solving one of these subtasks individually. Some recent work focused on solving a combination of two subtasks, e.g., extract... | [
"Sentiment Analysis",
"Term Extraction",
"Aspect-based Sentiment Analysis",
"Information Extraction & Text Mining"
] | [
78,
1,
23,
3
] |
http://arxiv.org/abs/2107.11768v1 | A Joint and Domain-Adaptive Approach to Spoken Language Understanding | Spoken Language Understanding (SLU) is composed of two subtasks: intent detection (ID) and slot filling (SF). There are two lines of research on SLU. One jointly tackles these two subtasks to improve their prediction accuracy, and the other focuses on the domain-adaptation ability of one of the subtasks. In this paper,... | [
"Low-Resource NLP",
"Responsible & Trustworthy NLP"
] | [
80,
4
] |
SCOPUS_ID:85078863096 | A Joint sentence scoring and selection framework for neural extractive document summarization | Extractive document summarization methods aim to extract important sentences to form a summary. Previous works perform this task by first scoring all sentences in the document then selecting most informative ones; while we propose to jointly learn the two steps with a novel end-To-end neural network framework. Specific... | [
"Language Models",
"Semantic Text Processing",
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
52,
72,
30,
47,
3
] |
SCOPUS_ID:85144015207 | A Joint-Training Two-Stage Method for Remote Sensing Image Captioning | Compared with remote sensing image (RSI) captioning methods based on the traditional encoder-decoder model, two-stage RSI captioning methods include an auxiliary remote sensing task to provide prior information, which enables them to generate more accurate descriptions. In previous two-stage RSI captioning methods, how... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Information Extraction & Text Mining",
"Captioning",
"Text Generation",
"Text Classification",
"Multimodality"
] | [
20,
52,
72,
24,
3,
39,
47,
36,
74
] |
SCOPUS_ID:85013036619 | A Journey of Bounty Hunters: Analyzing the Influence of Reward Systems on StackOverflow Question Response Times | Question and Answering (Q&A) platforms are an important source for information and a first place to go when searching for help. Q&A sites, like StackOverflow (SO), use reward systems to incentivize users to answer fast and accurately. In this paper we study and predict the response time for those questions on StackOver... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
SCOPUS_ID:85122653960 | A Judgment Method of Network News Value Orientation Based on Sentiment Analysis | Nowadays, recommendation algorithms are playing an increasingly important role in online news platforms. Current personalized recommendation algorithms aim to find connections between user characteristics and news to be recommended, so as to achieve accurate recommendations. The goal of the personalized recommendation ... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85072852226 | A Judicial Sentencing Method Based on Fused Deep Neural Networks | Nowadays, the judicial system has been hard to satisfy the growing judicial needs of the people. Therefore, the introduction of artificial intelligence into the judicial field is an inevitable trend. This paper incorporates deep learning into intelligent judicial sentencing and proposes a comprehensive network fusion m... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
https://aclanthology.org//W11-2045/ | A Just-in-Time Document Retrieval System for Dialogues or Monologues | [
"Natural Language Interfaces",
"Document Retrieval",
"Information Retrieval",
"Dialogue Systems & Conversational Agents"
] | [
11,
56,
24,
38
] | |
https://aclanthology.org//W18-4410/ | A K-Competitive Autoencoder for Aggression Detection in Social Media Text | We present an approach to detect aggression from social media text in this work. A winner-takes-all autoencoder, called Emoti-KATE is proposed for this purpose. Using a log-normalized, weighted word-count vector at input dimensions, the autoencoder simulates a competition between neurons in the hidden layer to minimize... | [
"Language Models",
"Semantic Text Processing",
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
52,
72,
17,
4
] |
SCOPUS_ID:78650009559 | A K-Nearest Neighbor Algorithm based on cluster in text classification | The K-Nearest Neighbor Algorithm (K-NN) is an important approach for automatic text classification. In this paper, cluster was applied In order to overcome the disadvantages of the traditional K-NN algorithm. First Clustering was utilized in training set through an improved K-mean approach to select the most representa... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Text Clustering"
] | [
3,
24,
36,
29
] |
SCOPUS_ID:84902176387 | A K-main routes approach to spatial network activity summarization | Data summarization is an important concept in data mining for finding a compact representation of a dataset. In spatial network activity summarization (SNAS), we are given a spatial network and a collection of activities (e.g., pedestrian fatality reports, crime reports) and the goal is to find \(k\) shortest paths tha... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85040554388 | A K-medoids based clustering scheme with an application to document clustering | Clustering is an important unsupervised data analysis technique, which divides data objects into clusters based on similarity. Clustering has been studied and applied in many different fields, including pattern recognition, data mining, decision science and statistics. Clustering algorithms can be mainly classified as ... | [
"Information Extraction & Text Mining",
"Text Clustering"
] | [
3,
29
] |
SCOPUS_ID:84857335867 | A K-mixture connective-strength-based approach to automatic text summarisation | This research focuses on developing a hybrid automatic text summarisation approach, KCS, to enhance the quality of summaries. KCS employs the K-mixture probabilistic model to establish term weight distributions in a statistical sense. It further identifies the lexical relations between nouns and nouns, as well as nouns... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:84905865743 | A K-nearest-neighbour based classifier for securities text categorization | Event-driven investments have gained great importance and popularity. Due to the importance of the timely and effective messages for successful investment, the automated categorization of documents into predefined labels has received an ever-increased attention in the recent years. This paper implements a new text docu... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:84994257442 | A KL divergence and DNN-based approach to voice conversion without parallel training sentences | We extend our recently proposed approach to cross-lingual TTS training to voice conversion, without using parallel training sentences. It employs Speaker Independent, Deep Neural Net (SIDNN) ASR to equalize the difference between source and target speakers and Kullback-Leibler Divergence (KLD) to convert spectral param... | [
"Multilinguality",
"Low-Resource NLP",
"Cross-Lingual Transfer",
"Information Extraction & Text Mining",
"Speech & Audio in NLP",
"Syntactic Text Processing",
"Multimodality",
"Text Generation",
"Text Clustering",
"Phonetics",
"Speech Recognition",
"Responsible & Trustworthy NLP"
] | [
0,
80,
19,
3,
70,
15,
74,
47,
29,
64,
10,
4
] |
SCOPUS_ID:84897977516 | A KNN based algorithm for text categorization | In the recent decade categorization of web texts has experienced increased attention. Huge amount of textual information available on the web emerged a need to find and obtain relevant information for strategically supported decisions. There are many machine learning algorithms dealing with text categorization and clas... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85073248887 | A KNOWLEDGE REPRESENTATION LANGUAGE for NATURAL LANGUAGE PROCESSING, SIMULATION and REASONING | OntoAgent is an environment that supports the cognitive modeling of societies of intelligent agents that emulate human beings. Like traditional intelligent agents, OntoAgent agents execute the core functionalities of perception, reasoning and action. Unlike most traditional agents, they engage in extensive "translation... | [
"Machine Translation",
"Semantic Text Processing",
"Representation Learning",
"Knowledge Representation",
"Text Generation",
"Reasoning",
"Multilinguality"
] | [
51,
72,
12,
18,
47,
8,
0
] |
SCOPUS_ID:85131257722 | A KNOWLEDGE/DATA ENHANCED METHOD FOR JOINT EVENT AND TEMPORAL RELATION EXTRACTION | Understanding temporal relations (TempRels) between events is an important task that could benefit many downstream NLP applications. This task inevitably faces the challenges of both a limited amount of high-quality training data and a very biased distribution of TempRels. These problems will substantially hurt the per... | [
"Event Extraction",
"Relation Extraction",
"Information Extraction & Text Mining"
] | [
31,
75,
3
] |
SCOPUS_ID:85131679253 | A Kaleidoscope of I-Positions: Chinese Volunteers’ Enactment of Teacher Identity in Australian Classrooms | This article explores the enactment of teacher identity by Chinese international students volunteering in Australian schools. Dialogical Self Theory offers a theoretical framework for understanding the intrapersonal and interpersonal nature of a teacher’s identity, but lacks an analytical tool for describing self-dialo... | [
"Discourse & Pragmatics",
"Natural Language Interfaces",
"Semantic Text Processing",
"Dialogue Systems & Conversational Agents"
] | [
71,
11,
72,
38
] |
SCOPUS_ID:84893035237 | A Kalman filter based human-computer interactive word segmentation system for ancient Chinese Texts | Previous research showed that Kalman filter based human-computer interaction Chinese word segmentation algorithm achieves an encouraging effect in reducing user interventions. This paper designs an improved statistical model for ancient Chinese texts, and integrates it with the Kalman filter based framework. An online ... | [
"Text Segmentation",
"Syntactic Text Processing"
] | [
21,
15
] |
SCOPUS_ID:84957801042 | A Kansei evaluation approach based on the technique of computing with words | Kansei evaluation plays a vital role in the implementation of Kansei engineering; however, it is difficult to quantitatively evaluate customer preferences of a product's Kansei attributes as such preferences involve human perceptual interpretation with certain subjectivity, uncertainty, and imprecision. An effective Ka... | [
"Information Extraction & Text Mining",
"Text Clustering"
] | [
3,
29
] |
SCOPUS_ID:51749084711 | A Kernel for measuring structural semantic similarities | Semantic similarity is nowadays one of the widely discussed topics in data mining, natural language processing and some related research fields. Semantic similarity between two entities usually comes into one's sight when tackling such issues. In this paper, however, we adopt such a standpoint that semantic similaritie... | [
"Semantic Text Processing",
"Semantic Similarity"
] | [
72,
53
] |
http://arxiv.org/abs/2210.05643v2 | A Kernel-Based View of Language Model Fine-Tuning | It has become standard to solve NLP tasks by fine-tuning pre-trained language models (LMs), especially in low-data settings. There is minimal theoretical understanding of empirical success, e.g., why fine-tuning a model with $10^8$ or more parameters on a couple dozen training points does not result in overfitting. We ... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85075837624 | A Key-Phrase Aware End2end Neural Response Generation Model | Previous Seq2Seq models for chitchat assume that each word in the target sequence has direct corresponding relationship with words in the source sequence, and all the target words are equally important. However, it is invalid since sometimes only parts of the response are relevant to the message. For models with the ab... | [
"Dialogue Response Generation",
"Language Models",
"Semantic Text Processing",
"Text Generation"
] | [
14,
52,
72,
47
] |
SCOPUS_ID:85129349261 | A Keylogging Inference Attack on Air-Tapping Keyboards in Virtual Environments | Enabling users to push the physical world's limits, augmented and virtual reality platforms opened a new chapter in perception. Novel immersive experiences resulted in the emergence of new interaction methods for virtual environments, which came with unprecedented security and privacy risks. This paper presents a keylo... | [
"Ethical NLP",
"Robustness in NLP",
"Responsible & Trustworthy NLP"
] | [
17,
58,
4
] |
SCOPUS_ID:85146420140 | A Keyphrase Extraction Method Based on Multi-feature Evaluation and Mask Mechanism | Keyphrase extraction aims to identify phrases in documents that contain core content. However, existing unsupervised keyphrase extraction models are limited to focusing on a single feature leading to biased results. In response to the above problems, it evaluates keyphrase scores through multiple features of semantic i... | [
"Language Models",
"Semantic Text Processing",
"Term Extraction",
"Information Extraction & Text Mining"
] | [
52,
72,
1,
3
] |
SCOPUS_ID:85124991818 | A Keyword Detection and Context Filtering Method for Document Level Relation Extraction | Relation extraction (RE) is the core link of downstream tasks, such as information retrieval, question answering systems, and knowledge graphs. Most of the current mainstream RE technologies focus on the sentence-level corpus, which has great limitations in practical applications. Moreover, the previously proposed mode... | [
"Language Models",
"Semantic Text Processing",
"Relation Extraction",
"Structured Data in NLP",
"Multimodality",
"Information Extraction & Text Mining"
] | [
52,
72,
75,
50,
74,
3
] |
SCOPUS_ID:85124369176 | A Keyword Extraction Method for Transportation Industry Standards based on improved TextRank | Facing the current standards of large scale and large quantity in transportation industry, how to efficiently extract standard keywords to provide professional services is a problem that needs to be solved in the industry at present. According to the text characteristics of transportation industry standards, this paper... | [
"Term Extraction",
"Information Extraction & Text Mining"
] | [
1,
3
] |
SCOPUS_ID:85024713009 | A Keyword Extraction Method for generating a User Profile in the Paper Collection and Sharing System MiDoc | In this paper, we propose a new keyword extraction method for generation a user profile using collected papers without using a large corpus. We assume that a user's interest exists in papers. Our method can extract keywords that can express user's interest in papers that user's interest exit. Our method can be used for... | [
"Term Extraction",
"Information Extraction & Text Mining"
] | [
1,
3
] |
SCOPUS_ID:85071856313 | A Keyword Extraction Scheme from CQI Based on Graph Centrality | Recently, most of the universities in Korea is doing a lecture evaluation survey every semester. The continuous quality improvement (CQI) report is one of the most popular lecture evaluation service systems, which able to summaries and analysis the mean of evaluation reports. Since 2016, education office allows CQI sys... | [
"Multimodality",
"Structured Data in NLP",
"Term Extraction",
"Information Extraction & Text Mining"
] | [
74,
50,
1,
3
] |
SCOPUS_ID:84866603493 | A Keyword-topic model for contextual advertising | Contextual advertising is a type of online advertising in which the placement of commercial ads within a web page depends on the relevance of the ads to the page content. A common approach to determine relevance is to score the match between ads and the content of the viewed page, for example, by simple keyword or synt... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85028028266 | A Khmer NER method based on conditional random fields fusing with Khmer entity characteristics constraints | In order to improve the performance of Khmer named entity recognition(NER), a NER method based on conditional random field (CRF) model fusing with Khmer entity characteristics constraints is proposed in this paper. First of all, we carried out analyses on the Khmer entity characteristics, summarized the constraint on t... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
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