Named Entity Filtering Based on Concept

In this paper, we introduce a novel technique for named en- tity ltering, focused on the analysis of word association networks. We present an approach for modelling concepts which are distinctively re- lated to specic named entity. We evaluated our approach in the context of the TREC Knowledge Base Acceleration track, and we obtained sig- nicantly

[1]  Ian Soboro.  Overview of the TREC 2004 Novelty Track , 2004 .

[2]  Andrew Trotman,et al.  Overview of INEX 2007 Link the Wiki Track , 2007, INEX.

[3]  Ian Soboroff,et al.  Overview of the TREC 2004 Novelty Track , 2004, TREC.

[4]  Hannu Toivonen,et al.  Lexical Creativity from Word Associations , 2012, 2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems.

[5]  Heng Ji,et al.  Knowledge Base Population: Successful Approaches and Challenges , 2011, ACL.

[6]  Thorsten Joachims,et al.  Making large-scale support vector machine learning practical , 1999 .

[7]  Michael Gamon.  Graph-Based Text Representation for Novelty Detection , 2006 .

[8]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[9]  Feng Niu,et al.  Building an Entity-Centric Stream Filtering Test Collection for TREC 2012 , 2012, TREC.

[10]  Rada Mihalcea,et al.  Wikify!: linking documents to encyclopedic knowledge , 2007, CIKM '07.

[11]  Valentin I. Spitkovsky,et al.  A Cross-Lingual Dictionary for English Wikipedia Concepts , 2012, LREC.

[12]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[13]  Christopher D. Manning,et al.  Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling , 2005, ACL.

[14]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[15]  Ralf Steinberger,et al.  A survey of methods to ease the development of highly multilingual text mining applications , 2011, Language Resources and Evaluation.

[16]  Ted Dunning,et al.  Accurate Methods for the Statistics of Surprise and Coincidence , 1993, CL.

[17]  Paul McNamee,et al.  The HLTCOE Approach to the TREC 2012 KBA Track , 2012, TREC.

[18]  Dedre Gentner,et al.  Why Nouns Are Learned before Verbs: Linguistic Relativity Versus Natural Partitioning. Technical Report No. 257. , 1982 .

[19]  Arjen P. de Vries,et al.  CWI at TREC 2012, KBA Track and Session Track , 2012, TREC.