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Combining Knowledge- and Corpus-based Word-Sense-Disambiguation Methods

A. Montoyo, A. Suarez, G. Rigau, M. Palomar
2005 The Journal of Artificial Intelligence Research  
We present two WSD methods based on two main methodological approaches in this research area: a knowledge-based method and a corpus-based method.  ...  Our hypothesis is that word-sense disambiguation requires several knowledge sources in order to solve the semantic ambiguity of the words.  ...  An earlier paper (Suárez & Palomar, 2002b) about the corpus-based method (subsection 3.2) was presented at COLING 2002.  ... 
doi:10.1613/jair.1529 fatcat:jwo2u42az5hhxbdpwbikq2saga

Word Sense Disambiguation Based on Perceptron Model

Zhang Chun-Xiang, Gao Xue-Yao, Lu Zhi-Mao
2016 International Journal of Database Theory and Application  
In this paper, a linear combination model based on multiple discriminative features is proposed to determine correct sense of an ambiguous word, in which morphology and part of speech in left and right  ...  Word sense disambiguation (WSD) is an important research topic in natural language processing field, which is very useful for machine translation and information retrieval.  ...  Acknowledgements This work is supported by China Postdoctoral Science Foundation Funded Project(2014M560249) and Natural Science Foundation of Heilongjiang Province of China(F2015041).  ... 
doi:10.14257/ijdta.2016.9.5.12 fatcat:mftw6wferna2bn27jy2bhfssce

Determine Word Sense Based on Semantic and Syntax Information

Zhang Chun-Xiang, Sun Lu-Rong, Gao Xue-Yao
2016 International Journal of Database Theory and Application  
Word sense disambiguation (WSD) plays an important role in natural language processing fields. Semantic category is semantic knowledge and part-of-speech is syntax knowledge.  ...  The training corpus in SemEval-2007: Task#5 is applied to optimize SVM and the optimized SVM is tested. Experimental results show that the performance of the proposed method is improved.  ...  Acknowledgement This work is supported by China Postdoctoral Science Foundation Funded Project(2014M560249) and Natural Science Foundation of Heilongjiang Province of China(F2015041).  ... 
doi:10.14257/ijdta.2016.9.2.03 fatcat:su5oapovuzdqxjnjgfukcaed2i

Numerical Simulation of Ambiguity Resolution in Multiple Information Streams Based on Network Machine Translation

Lei Wang, Qun Ai
2020 Complexity  
This method does not rely on professional domain knowledge and training corpus and only uses the frequency, mutual information, and boundary entropy information of the string in the test corpus to solve  ...  Using the naive Bayesian machine learning method and the feature vector set extracted and constructed by the Dice coefficient method, a semantic word disambiguation model based on semantics is realized  ...  to the Bayesian model to obtain a semantic sense disambiguation model based on semantic knowledge.  ... 
doi:10.1155/2020/7278085 fatcat:dhqlzzft4bchfkm5uca6mhepua

Knowledge-based and knowledge-lean methods combined in unsupervised word sense disambiguation

Antonio Jimeno Yepes, Alan R. Aronson
2012 Proceedings of the 2nd ACM SIGHIT symposium on International health informatics - IHI '12  
Due to the scarcity of training data, knowledge-based and knowledge-lean methods receive attention as disambiguation methods.  ...  We present preliminary results of the combination of knowledgebased and knowledge-lean unsupervised methods which improves the performance of knowledge-based methods between 3% and 8%.  ...  Jimeno-Yepes to the NLM Research Participation Program sponsored by the National Library of Medicine and administered by the Oak Ridge Institute for Science and Education.  ... 
doi:10.1145/2110363.2110449 dblp:conf/ihi/Jimeno-YepesA12 fatcat:khklixsv3bfvrofhilcopig2fq

Development of an Approach for Disambiguating Ambiguous Hindi postposition

Avneet Kaur
2010 International Journal of Computer Applications  
Word Sense Disambiguation (WSD) refers to the resolution of lexical semantic ambiguity and its goal is to attribute the correct senses to words in a given context.  ...  N-gram algorithm is used for extracting the words from the corpus.  ...  Combining unsupervised lexical knowledge methods for word sense " Unsupervised word sense disambiguation rivaling supervised methods", Yarowsky, D. (1995), this paper presents an unsupervised learning  ... 
doi:10.5120/939-1317 fatcat:vk5hl2okr5amhn3aizrng3rvym

Translation Selection by Combining Multiple Measures for Sense Disambiguation and Word Selection

HYUN AH LEE, JUNTAE YOON, GIL CHANG KIM
2003 International Journal of Computer Processing Of Languages  
Based on the 'word-to-sense and sense-to-word' relationship between a source word and its translations, our method selects translation through two levels: sense disambiguation of a source word and selection  ...  The first one is based on knowledge from a bilingual dictionary, and the others are calculated using statistics from a target language corpus.  ...  Our method that combines sense disambiguation and word selection with multiple measures is open to import any method and any knowledge for sense disambiguation and word selection.  ... 
doi:10.1142/s0219427903000905 fatcat:klwsd3omk5dbtb3fzz73gitdfi

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

Roshan Karwa, Manoj Chandak
2015 International Journal on Natural Language Computing  
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  ...  This paper presents a hybrid approach for resolving ambiguity in a sentence which is based on integrating lexical knowledge and world knowledge.  ...  To get the correct sense, knowledge based depends on the dictionaries. Agirre et al. [1] , 1996 proposed Word Sense Disambiguation with Conceptual Density method.  ... 
doi:10.5121/ijnlc.2015.4203 fatcat:m7vkoa65qrbbtmn7cfgvtrd5cq

Word Sense Disambiguation in Information Retrieval

Francis de la C. Fernández REYES, Exiquio C. Pérez LEYVA, Rogelio Lau FERNáNDEZ
2009 Intelligent Information Management  
This paper presents an approximated approach that combines not supervised algorithms by the use of a classifiers set, the result will be a learning algorithm based on unsupervised methods for word sense  ...  It begins with an introduction to word sense disambiguation concepts and then analyzes some unsupervised algorithms in order to extract the best of them, and combines them under a supervised approach making  ...  # disambiguated words Recall = # correctly disambiguated words The method we propose is based on the combination of various not supervised algorithms and baselines.  ... 
doi:10.4236/iim.2009.12018 fatcat:qy7t5kjmvrbupjgxlnjv3rjj7y

Combining corpus-derived sense profiles with estimated frequency information to disambiguate clinical abbreviations

Hua Xu, Peter D Stetson, Carol Friedman
2012 AMIA Annual Symposium Proceedings  
Furthermore, we developed a strategy to combine sense frequency information estimated from a clustering analysis with the profile-based method.  ...  In this study, we proposed a profile-based method that used dictated discharge summaries as an external source to automatically build sense profiles and applied them to disambiguate abbreviations in hospital  ...  Acknowledgement This study was supported by grants from the US NIH: NLM R01LM010681 (HX), R01LM8635 (CF), and R01LM010016 (CF).  ... 
pmid:23304376 pmcid:PMC3540457 fatcat:qvkthyylwzgo5a3ylhnhfdahsq

Unsupervised Approach to Word Sense Disambiguation in Malayalam

K.P. Sruthi Sankar, P.C. Reghu Raj, V. Jayan
2016 Procedia Technology - Elsevier  
Since the sense of a word depends on its context of use, disambiguation process requires the understanding of word knowledge.  ...  Word Sense Disambiguation (WSD) is the task of identifying the correct sense of a word in a specific context when the word has multiple meaning.  ...  We would like to gratefully acknowledge to all staff members in the department of Computer Science and Engineering, Government Engineering College, Palakkad, for their immense support.  ... 
doi:10.1016/j.protcy.2016.05.106 fatcat:xdmg3pgokzdnnnbymmnsl5g3c4

Word Sense disambiguation based on stretchable matching of the semantic template

Wei Wang, ,School of Computer Science and Technology, Dalian University of Technology, No.2 Linggong Road, Ganjingzi District, Dalian City, Liaoning Province, China, Degen Huang, Haitao Yu, ,Faculty of Library, Information and Media Science, University of Tsukuba, Tsukuba, Japan
2019 Mathematical Foundations of Computing  
We have applied this method to word sense disambiguation in the natural language processing field.  ...  In the same case of using only the SemCor corpus, the result of our system is very close to the best result of existing systems , which shows the effectiveness of new proposed method.  ...  The knowledge-based method, which extracts information from electronic dictionaries or other knowledge sources for disambiguation, mainly relies on the scale and details of the words that are described  ... 
doi:10.3934/mfc.2020022 fatcat:rny2e46x6jetnisxdmy6oq3iz4

Word Sense Disambiguation with Automatically Acquired Knowledge

Ping Chen, Chris Bowes, Wei Ding, Max Choly
2012 IEEE Intelligent Systems  
Such an automatic approach overcomes the knowledge acquisition bottleneck and makes broad-coverage word sense disambiguation feasible in practice.  ...  Word sense disambiguation is the process of determining which sense of a word is used in a given context.  ...  ACKNOWLEDGMENTS This work is partially funded by NSF grant DUE 0737408 and CNS 0851984. This paper contains proprietary information protected under a pending U.S. patent (No. 61/121,015) .  ... 
doi:10.1109/mis.2010.134 fatcat:iq4ywzyuvnctxmtfsgimgs453e

Knowledge-Based Biomedical Word Sense Disambiguation: An Evaluation and Application to Clinical Document Classification

Vijay N. Garla, Cynthia Brandt
2012 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology  
Acknowledgements We are especially thankful to the NLM and others who developed the Word Sense Disambiguation benchmarks.  ...  This work was supported in part by NIH grant T15 LM07056 from the National Library of Medicine, CTSA grant number UL1 RR024139 from the NIH National Center for Advancing Translational Sciences (NCATS), and  ...  without word sense disambiguation (WSD) cTAKES, clinical Text Analysis and Knowledge Extraction System.  ... 
doi:10.1109/hisb.2012.12 dblp:conf/hisb/GarlaB12 fatcat:rcxw74xrarchvawo62ezccvofa

Integrate Chinese Semantic Knowledge into Word Sense Disambiguation

Chun-Xiang Zhang, Lu-Rong Sun, Xue-Yao Gao, Zhi-Mao Lu, Yong Yue
2015 International Journal of Hybrid Information Technology  
A new method of word sense disambiguation is proposed with semantic information of left word unit and right word unit. The classifier of word sense disambiguation is built based on bayesian model.  ...  SemEval-2007: Task#5 is used as training corpus and test corpus.  ...  /w Semantic lexicon gives semantic categories of words and provides rich semantic knowledge for word sense disambiguation.  ... 
doi:10.14257/ijhit.2015.8.4.13 fatcat:a5gz3qrk2rcppekxmnshhfx27y
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