Effective Features for Disambiguation of Turkish Verbs

This paper summarizes the results of some experiments for finding the effective features for disambiguation of Turkish verbs. Word sense disambiguation is a current area of investigation in which verbs have the dominant role. Generally verbs have more senses than the other types of words in the average and detecting these features for verbs may lead to some improvements for other word types. In this paper we have considered only the syntactical features that can be obtained from the corpus and tested by using some famous machine learning algorithms. Keywords—Word sense disambiguation, feature selection. I. INTRODUCTION

[1]  Claire Cardie,et al.  A Case-Based Approach to Knowledge Acquisition for Domain-Specific Sentence Analysis , 1993, AAAI.

[2]  David Yarowsky,et al.  Hierarchical Decision Lists for Word Sense Disambiguation , 2000, Comput. Humanit..

[3]  Hwee Tou Ng,et al.  Integrating Multiple Knowledge Sources to Disambiguate Word Sense: An Exemplar-Based Approach , 1996, ACL.

[4]  Hwee Tou Ng,et al.  Exemplar-Based Word Sense Disambiguation” Some Recent Improvements , 1997, EMNLP.

[5]  David Yarowsky,et al.  One Sense per Collocation , 1993, HLT.

[6]  Ted Pedersen,et al.  A New Supervised Learning Algorithm for Word Sense Disambiguation , 1997, AAAI/IAAI.

[7]  Lluís Màrquez i Villodre,et al.  Naive Bayes and Exemplar-based Approaches to Word Sense Disambiguation Revisited , 2000, ECAI.

[8]  Hwee Tou Ng,et al.  An Empirical Evaluation of Knowledge Sources and Learning Algorithms for Word Sense Disambiguation , 2002, EMNLP.

[9]  David W. Aha,et al.  Feature Selection for Case-Based Classification of Cloud Types: An Empirical Comparison , 1994 .

[10]  Alon Itai,et al.  Word Sense Disambiguation Using a Second Language Monolingual Corpus , 1994, CL.

[11]  Rada Mihalcea,et al.  Instance Based Learning with Automatic Feature Selection Applied to Word Sense Disambiguation , 2002, COLING.

[12]  Adam Kilgarriff,et al.  SENSEVAL: an exercise in evaluating world sense disambiguation programs , 1998, LREC.

[13]  Hwee Tou Ng,et al.  Corpus-Based Approaches to Semantic Interpretation in Natural Language Processing , 1997 .

[14]  Massimiliano Ciaramita,et al.  Multi-component Word Sense Disambiguation , 2004, SENSEVAL@ACL.

[15]  Kenneth Ward Church,et al.  Work on Statistical Methods for Word Sense Disambiguation , 1992 .

[16]  Kemal Oflazer,et al.  The Annotation Process in the Turkish Treebank , 2003, LINC@EACL.

[17]  Kemal Oflazer,et al.  Building a wordnet for Turkish , 2004 .

[18]  Pedro M. Domingos Control-Sensitive Feature Selection for Lazy Learners , 1997, Artificial Intelligence Review.

[19]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[20]  Edward F. Kelly,et al.  Computer recognition of English word senses , 1975 .

[21]  Claire Cardie,et al.  Automating Feature Set Selection for Case-Based Learning of Linguistic Knowledge , 1996, EMNLP.

[22]  Ellen M. Voorhees,et al.  Corpus-Based Statistical Sense Resolution , 1993, HLT.

[23]  David Yarowsky,et al.  Word-Sense Disambiguation Using Statistical Models of Roget’s Categories Trained on Large Corpora , 2010, COLING.

[24]  Janyce Wiebe,et al.  Decomposable Modeling in Natural Language Processing , 1999, CL.

[25]  Hinrich Schütze,et al.  Information retrieval based on word senses , 1995 .

[26]  Andrew W. Moore,et al.  Efficient Algorithms for Minimizing Cross Validation Error , 1994, ICML.

[27]  David Yarowsky,et al.  DECISION LISTS FOR LEXICAL AMBIGUITY RESOLUTION: Application to Accent Restoration in Spanish and French , 1994, ACL.

[28]  Walter Daelemans,et al.  Memory-Based Word Sense Disambiguation , 2000, Comput. Humanit..

[29]  Raymond J. Mooney,et al.  Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning , 1996, EMNLP.

[30]  Janyce Wiebe,et al.  Word-Sense Disambiguation Using Decomposable Models , 1994, ACL.

[31]  Stamou Sofia Oflazer,et al.  BALKANET: A Multilingual Semantic Network for Balkan Languages , 2001 .

[32]  Ted Pedersen,et al.  A Decision Tree of Bigrams is an Accurate Predictor of Word Sense , 2001, NAACL.