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Helping Term Sense Disambiguation with Active Learning

Pierre André Ménard, Caroline Barrière, Jean Quirion
2015 International Conference on Terminology and Artificial Intelligence  
Automatic term sense disambiguation, as a possible solution, requires human annotation to feed a supervised learning algorithm.  ...  We suggest the use of active learning and implement it within an annotation platform as a way of reducing annotation time.  ...  Terminometrics active-learning platform We developed an annotation platform, shown in Figure 5 , to facilitate terminometrics studies with an active learning component for term disambiguation.  ... 
dblp:conf/tia/MenardBQ15 fatcat:vggdgnf2hnad3julpqezsglgjq

Wiki sense bag creation using multilingual word sense disambiguation

Shreya Patankar, Madhura Phadke, Satish Devane
2022 IAES International Journal of Artificial Intelligence (IJ-AI)  
Corpora and create two bags namely ontological bag and wiki sense bag to generate the senses with highest similarity.  ...  Generation of sense annotated corpus for multilingual word sense disambiguation is out of reach for most languages even if resources are available.  ...  It helps to generate a similarity score which Int J Artif Intell ISSN: 2252-8938 Wiki sense bag creation using multilingual word sense disambiguation (Shreya Patankar) 323 helps in the disambiguation process  ... 
doi:10.11591/ijai.v11.i1.pp319-326 fatcat:tvbh6zjzrvf3dpsfnff76te6hy

Effects of information and machine learning algorithms on word sense disambiguation with small datasets

Gondy Leroy, Thomas C. Rindflesch
2005 International Journal of Medical Informatics  
Current approaches to word sense disambiguation use (and often combine) various machine learning techniques.  ...  to inaccuracies in the gold standard, leading to varied performance of word sense disambiguation techniques.  ...  Acknowledgements We thank the NLM experts who evaluated the medical terms, Halil Kilicoglu and Jim Mork for their assistance in making the data accessible, and Olivier Bodenreider for his suggestions.  ... 
doi:10.1016/j.ijmedinf.2005.03.013 pmid:15897005 fatcat:bohv76zvx5fuzjms7brcpmzzcu

WORD SENSE DISAMBIGUATION IN THE HINDI LANGUAGE: NEURAL NETWORK APPROACH

Sailendra Kumar, Rakesh Kumar
2021 International Journal of Technical Research & Science  
Hindi Word Sense Disambiguation (HWSD) system used to extract ambiguity from the Hindi language.  ...  It also helps in collecting information and helps in dealing with different software's.  ...  APPROACHES AND METHODS TO HWSD There are two ways to disambiguate words that are followed for Word Sense Disambiguation, machine learning methods and knowledge-based methods.  ... 
doi:10.30780/specialissue-icaaset021/014 fatcat:ljpdv753dnfsfdbneuvegozaye

Metaheuristic for Word Sense Disambiguation: a Review

Wafaa AL-Saiagh, Sabrina Tiun, Ahmed AL-Saffar, Suryanti Awang, A. S. Al-khaleefa
2018 International Journal of Engineering & Technology  
Word Sense Disambiguation (WSD) is the process of determining the exact sense of a particular word in accordance to the context in a computational manner.  ...  With the complexity of human language, WSD came up to solve the problem behind the ambiguity between senses in which a single word would yield different meaning.  ...  Introduction In a given text, the most appropriate senses are assigned to words with the help of word sense disambiguation (WSD) [58] .  ... 
doi:10.14419/ijet.v7i3.20.20586 fatcat:ormyo4yjonehjmg4tg5aeyzyba

Detection and Analysis of Stress using Machine Learning Techniques

2019 International Journal of Engineering and Advanced Technology  
Keywords: Stress Detection, Data Mining, TensiStrength, word sense disambiguation.  ...  The major drawback of machine translation is Word Sense Disambiguation. There is a fact that a single word can have multiple meanings or "senses."  ...  Such words with multiple meaning or senses are called ambiguous word and the process of finding the exact sense of an ambiguous word for a particular context is called word sense disambiguation [10] .  ... 
doi:10.35940/ijeat.f8573.109119 fatcat:qjqljdq3pnh5vfcmojixjyccee

An Intelligent Hybrid Approach for Improving Recall in Electronic Discovery

Eniafe F. Ayetiran
2013 International Conference on Legal Knowledge and Information Systems  
This approach takes ideas from Natural Language Processing (Word sense disambiguation) and Information Retrieval in enhancing retrieval of responsive documents using the semantics of query terms instead  ...  to help lawyers and their clients during litigations.  ...  Sense disambiguation of user query. b. Expansion of query with semantically related terms to the query terms c.  ... 
dblp:conf/jurix/Ayetiran13 fatcat:hysqsmxpgzhwtdgxlghaq4gav4

A Survey on Word Sense Disambiguation

Rohit Giyanani
2013 IOSR Journal of Computer Engineering  
The process of identifying the correct sense of the word in a particular sentence is called Word Sense Disambiguation.  ...  Ambiguity has been always interwoven with human language and its evolution.  ...  Content analysis using WSD can help in classification of data with as per user requirements. 4.  ... 
doi:10.9790/0661-1463033 fatcat:vwindvwfl5dmvl6iefu7krat6i

An Hybrid Approach to Word Sense Disambiguation with and Without Learned Knowledge

Roshan Karwa, Manoj Chandak
2015 International Journal on Natural Language Computing  
Researchers tried for unsupervised and knowledge based learning approaches however such approaches have not proved more helpful.  ...  Word Sense Disambiguation is a classification of meaning of word in a precise context which is a tricky task to perform in Natural Language Processing which is used in application like machine translation  ...  module with active feature selection.  ... 
doi:10.5121/ijnlc.2015.4203 fatcat:m7vkoa65qrbbtmn7cfgvtrd5cq

Disambiguating proteins, genes, and RNA in text: a machine learning approach

V. Hatzivassiloglou, P. A. Duboue, A. Rzhetsky
2001 Bioinformatics  
Three machine learning algorithms and several extended ways for defining contextual features for disambiguation are examined, and a fully unsupervised manner for obtaining training examples is proposed  ...  We present an automated system for assigning protein, gene, or mRNA class labels to biological terms in free text.  ...  ACKNOWLEDGMENTS We thank Pavel Morozov for implementing the article downloading software, Wubin Weng for helping transcribe the experts' annotations, and Shawn M.  ... 
doi:10.1093/bioinformatics/17.suppl_1.s97 pmid:11472998 fatcat:m7gctkzvr5c3lpkcwg5yuegj2y

Learning to Link Grammar and Encyclopedic Information of Assist ESL Learners

Jhih-Jie Chen, Chingyu Yang, Peichen Ho, Ming Chiao Tsai, Chia-Fang Ho, Kai-Wen Tuan, Chung-Ting Tsai, Wen-Bin Han, Jason Chang
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations  
The method involves word sense disambiguation on target words, automatically parsing the sentences in a large-scale corpus, automatically generating grammar patterns, collocations, examples, and quizzes  ...  Evaluation on a set of target words shows that the method has reasonably good performance in terms of generating useful and correct information for vocabulary learning.  ...  Identifying the intended word sense relevant to the context has long been an active topic of word sense disambiguation (WSD) research.  ... 
doi:10.18653/v1/p19-3034 dblp:conf/acl/ChenYHTHTTHC19 fatcat:a3hckkadjnbtto56gc2qkzhuya

Word Sense Discrimination [chapter]

2017 Encyclopedia of Machine Learning and Data Mining  
with machine learning algorithms.  ...  The word sense disambiguation literature describes experiments with a large number of machine learning algorithms, including decision lists (Yarowsky 2000), instance-based learning (Ng and Lee 1996), Naïve  ... 
doi:10.1007/978-1-4899-7687-1_883 fatcat:kruczwhjlndyjl3zesk2qqxmoi

A Design and Development of Word Sense Disambiguation Algorithm for English Language Understanding for Database Access

Munusamy
2011 Journal of Computer Science  
Results: This object-net approach disambiguates original text with high precision of 96% of the verbs and 97% of nouns for data extraction from the database and reporting in terms of graphs.  ...  Problem statement: This study attempts to present an object-net method for word sense disambiguation.  ...  RESULTS Object-net approach for database extraction: We illustrate here the Object-Net disambiguation algorithm with the help of previous example "I need the student report that joined on 04 November  ... 
doi:10.3844/jcssp.2011.1612.1618 fatcat:wf7vvbwhr5ftrj7jw2j7vgoghe

Neural Semantic Role Labeling using Verb Sense Disambiguation

Domenico Alfano, Roberto Abbruzzese, Donato Cappetta
2019 Italian Conference on Computational Linguistics  
VSD is a sub-problem of the Word Sense Disambiguation (WSD) problem, that tries to identify in which sense a polysemic word is used in a given sentence.  ...  Then, we explore different solutions in order to achieve better results by approaching to Verb-Sense Disambiguation (VSD).  ...  Specifically, Babelfy performs the tasks of mul- tilingual Word Sense Disambiguation and Entity Linking.  ... 
dblp:conf/clic-it/AlfanoAC19 fatcat:6s3rr7k2areclk7dvb7mhhkqpu
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