Vector Space Representation of Concepts Using Wikipedia Graph Structure

We introduce a vector space representation of concepts using Wikipedia graph structure to calculate semantic relatedness. The proposed method starts from the neighborhood graph of a concept as the primary form and transfers this graph into a vector space to obtain the final representation. The proposed method achieves state of the art results on various relatedness datasets.

[1]  Gerhard Weikum,et al.  KORE: keyphrase overlap relatedness for entity disambiguation , 2012, CIKM.

[2]  Terrence Adam,et al.  Semantic Similarity and Relatedness between Clinical Terms: An Experimental Study. , 2010, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[3]  R. Lougee-Heimer,et al.  The Common Optimization INterface for Operations Research: Promoting open-source software in the operations research community , 2003 .

[4]  Ian H. Witten,et al.  Learning to link with wikipedia , 2008, CIKM '08.

[5]  Eneko Agirre,et al.  A Study on Similarity and Relatedness Using Distributional and WordNet-based Approaches , 2009, NAACL.

[6]  Ted Pedersen,et al.  Measures of semantic similarity and relatedness in the biomedical domain , 2007, J. Biomed. Informatics.

[7]  Evangelos E. Milios,et al.  Vector Embedding of Wikipedia Concepts and Entities , 2017, NLDB.

[8]  Doug Downey,et al.  Local and Global Algorithms for Disambiguation to Wikipedia , 2011, ACL.

[9]  Vlado Keselj,et al.  Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text , 2015, CICLing.

[10]  Xuelong Li,et al.  A survey of graph edit distance , 2010, Pattern Analysis and Applications.

[11]  Simone Paolo Ponzetto,et al.  Knowledge Derived From Wikipedia For Computing Semantic Relatedness , 2007, J. Artif. Intell. Res..

[12]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[13]  Ben Hachey,et al.  Entity Disambiguation with Web Links , 2015, TACL.

[14]  Xiaoying Gao,et al.  CPRel: Semantic Relatedness Computation Using Wikipedia based Context Profiles , 2013, Res. Comput. Sci..

[15]  Dániel Fogaras.  Where to Start Browsing the Web? , 2003, IICS.

[16]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[17]  Ziv Bar-Yossef,et al.  Local approximation of PageRank and reverse PageRank , 2008, SIGIR '08.

[18]  Nevena Lazic,et al.  Plato: A Selective Context Model for Entity Resolution , 2015, TACL.

[19]  Leo Katz,et al.  A new status index derived from sociometric analysis , 1953 .

[20]  Ian H. Witten,et al.  An effective, low-cost measure of semantic relatedness obtained from Wikipedia links , 2008 .

[21]  M. Fiedler.  Laplacian of graphs and algebraic connectivity , 1989 .

[22]  G. Miller,et al.  Contextual correlates of semantic similarity , 1991 .

[23]  Eneko Agirre,et al.  Studying the Wikipedia Hyperlink Graph for Relatedness and Disambiguation , 2015, ArXiv.

[24]  Hector Garcia-Molina,et al.  Combating Web Spam with TrustRank , 2004, VLDB.

[25]  John B. Goodenough,et al.  Contextual correlates of synonymy , 1965, CACM.

[26]  Silviu Cucerzan,et al.  Large-Scale Named Entity Disambiguation Based on Wikipedia Data , 2007, EMNLP.

[27]  Eneko Agirre,et al.  WikiWalk: Random walks on Wikipedia for Semantic Relatedness , 2009, Graph-based Methods for Natural Language Processing.

[28]  Jon Kleinberg,et al.  Authoritative sources in a hyperlinked environment , 1999, SODA '98.

[29]  Ted Pedersen,et al.  Towards a framework for developing semantic relatedness reference standards , 2011, J. Biomed. Informatics.

[30]  Ganesh Ramakrishnan,et al.  Collective annotation of Wikipedia entities in web text , 2009, KDD.