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Four Methods for Supervised Word Sense Disambiguation [chapter]

Kinga Schumacher
Lecture Notes in Computer Science  
This paper describes four novel supervised disambiguation methods which adapt some familiar algorithms.  ...  Word sense disambiguation is the task to identify the intended meaning of an ambiguous word in a certain context, one of the central problems in natural language processing.  ...  The four supervised disambiguation methods have been developed in the context of the EU-project NEWS (News Engine Web Services,  ... 
doi:10.1007/978-3-540-73351-5_28 fatcat:zck3vj5uxjfffgwk2eqljxwbmi

A Learning-Based Approach for Biomedical Word Sense Disambiguation

Hisham Al-Mubaid, Sandeep Gungu
2012 The Scientific World Journal  
The main limitation with supervised methods is the need for a corpus of manually disambiguated instances of the ambiguous words.  ...  The proposed method utilizes the interaction model (mutual information) between the context words and the senses of the target word to induce reliable learning models for sense disambiguation.  ...  In this paper, we present and evaluate a supervised method for biomedical word sense disambiguation.  ... 
doi:10.1100/2012/949247 pmid:22666174 pmcid:PMC3361294 fatcat:2vx3kqpbsbb53c6bdusnb34tde

Word Sense Disambiguation by Semi-supervised Learning [chapter]

Zheng-Yu Niu, Donghong Ji, Chew-Lim Tan, Lingpeng Yang
2005 Lecture Notes in Computer Science  
(bilingual bootstrapping) for word sense disambiguation.  ...  We evaluated a semi-supervised learning algorithm, local and global consistency algorithm, on widely used benchmark corpus for word sense disambiguation.  ...  Conclusion and Future Work In this paper we investigated the application of a semi-supervised learning algorithm for word sense disambiguation.  ... 
doi:10.1007/978-3-540-30586-6_25 fatcat:ecmtsmbgxrbsritp6stkvmfama

Lexical Disambiguation of Arabic Language: An Experimental Study

Laroussi Merhben, Anis Zouaghi, Mounir Zrigui
2012 POLIBITS Research Journal on Computer Science and Computer Engineering With Applications  
In this paper we test some supervised algorithms that most of the existing related works of word sense disambiguation have cited.  ...  words.  ...  We can presume that the supervised works are more satisfactory for the task of Arabic Word Sense Disambiguation. III.  ... 
doi:10.17562/pb-46-5 fatcat:2nmk3kaw6bfkfenefivr5au4me

TWE‐WSD: An effective topical word embedding based word sense disambiguation

Lianyin Jia, Jilin Tang, Mengjuan Li, Jinguo You, Jiaman Ding, Yinong Chen
2021 CAAI Transactions on Intelligence Technology  
Word embedding has been widely used in word sense disambiguation (WSD) and many other tasks in recent years for it can well represent the semantics of words.  ...  Instead of generating a single word vector (WV) for each word, TWE-WSD generates a topical WV for each word under each topic.  ...  was partially supported by the National Natural Science Foundation of China (61562054), the Fund of China Scholarship Council (201908530036) and the Talents Introduction Project of Guangxi University for  ... 
doi:10.1049/cit2.12006 fatcat:zzbdxvi355c3bpt3zvukgzyjru

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.  ...  Taghipour, [61] studies two different methods of integrating word embeddings in a word sense disambiguation environment, and also assesses these two methods for all-words tasks, some SensEval/ SemEval  ... 
doi:10.14419/ijet.v7i3.20.20586 fatcat:ormyo4yjonehjmg4tg5aeyzyba

SemEval-2010 Task 17: All-Words Word Sense Disambiguation on a Specific Domain

Eneko Agirre, Oier Lopez de Lacalle, Christiane Fellbaum, Shu-Kai Hsieh, Maurizio Tesconi, Monica Monachini, Piek Vossen, Roxanne Segers
2010 International Workshop on Semantic Evaluation  
Domain portability and adaptation of NLP components and Word Sense Disambiguation systems present new challenges.  ...  This task presented all-words datasets on the environment domain for WSD in four languages (Chinese, Dutch, English, Italian). 11 teams participated, with supervised and knowledge-based systems, mainly  ...  Kyoto: This system participated in all four languages, with a free reimplementation of the domain-specific knowledge-based method for WSD presented in .  ... 
dblp:conf/semeval/AgirreLFHTMVS10 fatcat:epw6uuziwnbstkuii5euqdpzra

Word Sense Disambiguation Based on Perceptron Model

Zhang Chun-Xiang, Gao Xue-Yao, Lu Zhi-Mao
2016 International Journal of Database Theory and Application  
Word sense disambiguation (WSD) is an important research topic in natural language processing field, which is very useful for machine translation and information retrieval.  ...  Experiments show that the WSD performance is improved after the proposed method is applied.  ...  Zhong develops an English all-word WSD system with java in which a supervised learning method is adopted. And this system is an extensible and flexible platform for researchers [2] .  ... 
doi:10.14257/ijdta.2016.9.5.12 fatcat:mftw6wferna2bn27jy2bhfssce


Sailendra Kumar, Rakesh Kumar
2021 International Journal of Technical Research & Science  
The four main approaches, which are commonly used, are knowledge-based, Supervised, Semi-Supervised, and Unsupervised.  ...  Hindi Word Sense Disambiguation (HWSD) system used to extract ambiguity from the Hindi language.  ...  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

A Semi-Supervised method for Persian homograph Disambiguation

Noushin Riahi, Fatemeh Sedghi
2012 20th Iranian Conference on Electrical Engineering (ICEE2012)  
One of the major challenges in the most natural languages processing (NLP) tasks such as machine translation, text to speech and text mining is Word Sense Disambiguation (WSD).  ...  Supervised methods are the most common solutions for WSD. However, they need large tagged corpuses which are not available in some languages such as Persian.  ...  This problem is often referred to as word sense disambiguation (WSD).  ... 
doi:10.1109/iraniancee.2012.6292453 fatcat:4kwwj2quy5g6pkrku3hcdujg54

Learning model order from labeled and unlabeled data for partially supervised classification, with application to word sense disambiguation

Zheng-Yu Niu, Dong-Hong Ji, Chew Lim Tan
2007 Computer Speech and Language  
Our experimental results on benchmark corpora for word sense disambiguation task indicate that this model order identification algorithm with the extended label propagation algorithm as the base classifier  ...  Previous partially supervised classification methods can partition unlabeled data into positive examples and negative examples for a given class by learning from positive labeled examples and unlabeled  ...  possible sense, e.g. supervised sense disambiguation methods, and semi-supervised sense disambiguation methods.  ... 
doi:10.1016/j.csl.2007.02.001 fatcat:vqiahbvpdvdchdxzlimb42ps7q

An Experimental Study on Unsupervised Graph-based Word Sense Disambiguation [chapter]

George Tsatsaronis, Iraklis Varlamis, Kjetil Nørvåg
2010 Lecture Notes in Computer Science  
Recent research works on unsupervised word sense disambiguation report an increase in performance, which reduces their handicap from the respective supervised approaches for the same task.  ...  Furthermore, it analyzes the levels of inter-agreement in the sense selection level, giving further insight on how these methods could be employed in an unsupervised ensemble for word sense disambiguation  ...  , both supervised and unsupervised, offering an experimental survey of the current top methods in word sense disambiguation, and (d) analysis of the methods inter-agreement in the sense selection level  ... 
doi:10.1007/978-3-642-12116-6_16 fatcat:d5nwat7k2bcf5hxfr3seousix4

Supervised Word Sense Disambiguation with Recurrent Neural Network Model

2019 International Journal of Engineering and Advanced Technology  
Disambiguating words is a branch of artificial intelligence that deals with natural language processing.  ...  There are four different suggested approaches to clutter as the knowledge-dependent approach and the machine learning based models which are further classified as supervised, semi-supervised and unpublished  ...  To reduce this problem and increase computer intelligence, we propose our research for word sense disambiguation.  ... 
doi:10.35940/ijeat.b3391.129219 fatcat:ywfk26vnhbc2dmzl254piovjoa

Semi-supervised Learning with Induced Word Senses for State of the Art Word Sense Disambiguation

Osman Başkaya, David Jurgens
2016 The Journal of Artificial Intelligence Research  
for all words.  ...  Word Sense Disambiguation (WSD) aims to determine the meaning of a word in context, and successful approaches are known to benefit many applications in Natural Language Processing.  ...  Acknowledgments We thank Mohammad Taher Pilehvar for many thoughtful discussions and his assistance with the pseudoword dataset. We also thank the reviewers for their comments and suggestions.  ... 
doi:10.1613/jair.4917 fatcat:w2xovb6f5jgtpnjrf77s7amogm

Query Expansion using Semantic Network for Information Retrieval in Telugu Language

2019 International journal of recent technology and engineering  
So to avoid this, proposed method Word Sense Disambiguation (WSD) is used, which is related to NLP Natural Language Processing and Artificial Intelligence AI.  ...  Our proposed query expansion technique is Word Sense Disambiguation. This is to find the correct sense of the ambiguous word in regional Telugu language.  ...  Word Sense Disambiguation Approaches to WSD are classified as supervised, unsupervised, and knowledge-based methods. In Telugu Language word sense disambiguation is at infant level.  ... 
doi:10.35940/ijrte.b1586.078219 fatcat:sddyynudvrcmvne5eufp4d6jhm
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