SnS: A Novel Word Sense Induction Method

The paper is devoted to the word sense induction problem. We propose a knowledge-poor method, called SenseSearcher (SnS), which induces senses of words from text corpora, based on closed frequent sets. The algorithm discovers a hierarchy of senses, rather than a flat list of concepts, so the results are easier to comprehend. We have evaluated the SnS quality by performing experiments for web search result clustering task with the datasets from SemEval-2013 Task 11.

[1]  Mohammed J. Zaki,et al.  CHARM: An Efficient Algorithm for Closed Itemset Mining , 2002, SDM.

[2]  Steffen Staab,et al.  ECAI'2000 Workshop on Ontology Learning, Proceedings of the First Workshop on Ontology Learning OL'2000, Berlin, Germany, August 25, 2000. Held in conjunction with the 14th European Conference on Artificial Intelligence ECAI'2000, Berlin, Germany , 2000, ECAI Workshop on Ontology Learning.

[3]  T. Landauer,et al.  A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge. , 1997 .

[4]  Mirella Lapata,et al.  Bayesian Word Sense Induction , 2009, EACL.

[5]  Eneko Agirre,et al.  UBC-AS: A Graph Based Unsupervised System for Induction and Classification , 2007, SemEval@ACL.

[6]  Patrick Pantel,et al.  Discovering word senses from text , 2002, KDD.

[7]  Roberto Navigli,et al.  Word sense disambiguation: A survey , 2009, CSUR.

[8]  Ted Pedersen,et al.  Knowledge Lean Word-Sense Disambiguation , 1997, AAAI/IAAI.

[9]  Roberto Navigli,et al.  SemEval-2013 Task 11: Word Sense Induction and Disambiguation within an End-User Application , 2013, SemEval@NAACL-HLT.

[10]  Steffen Staab,et al.  Discovering Conceptual Relations from Text , 2000, ECAI.

[11]  Ian Witten,et al.  Data Mining , 2000 .

[12]  Marzena Kryszkiewicz,et al.  Discovering Word Meanings Based on Frequent Termsets , 2007, MCD.

[13]  Jean Véronis,et al.  HyperLex: lexical cartography for information retrieval , 2004, Comput. Speech Lang..

[14]  Tomasz Nykiel,et al.  Word Sense Discovery for Web Information Retrieval , 2008, 2008 IEEE International Conference on Data Mining Workshops.

[15]  Chris Cornelis,et al.  Rough Sets and Intelligent Systems Paradigms , 2014, Lecture Notes in Computer Science.

[16]  Djamel A. Zighed,et al.  Mining Complex Data, ECML/PKDD 2007 Third International Workshop, MCD 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers , 2008, MCD.

[17]  Rada Mihalcea,et al.  Automatic generation of a coarse grained WordNet , 2001, HTL 2001.

[18]  Roger K. Moore.  Computer Speech and Language , 1986 .

[19]  Roberto Navigli,et al.  Clustering and Diversifying Web Search Results with Graph-Based Word Sense Induction , 2013, CL.

[20]  George A. Miller,et al.  Using a Semantic Concordance for Sense Identification , 1994, HLT.

[21]  Marzena Kryszkiewicz,et al.  Discovering Compound and Proper Nouns , 2007, RSEISP.

[22]  Dominic Widdows,et al.  Discovering Corpus-Specific Word Senses , 2003, EACL.

[23]  Hinrich Schütze,et al.  Automatic Word Sense Discrimination , 1998, Comput. Linguistics.

[24]  Felix Naumann,et al.  Data fusion , 2009, CSUR.

[25]  Mohammed J. Zaki.  Closed Itemset Mining and Non-redundant Association Rule Mining. , 2009 .