Semantic Relatedness Measures in Ontologies Using Information Content and Fuzzy Set Theory

The success of the semantic Web is linked with the use of ontologies on the semantic Web. Ontologies help systems understand the meaning of information and can serve as the interface to the inferencing layer of the semantic Web. An increasingly important task is to determine a degree or measure of semantic relatedness between concepts within and across ontologies. This paper presents an overview of such measures using several examples found in the research literature. The relationship between a distance-based network semantic relatedness measure and an information theoretic measure is shown for the first time by using Tversky's set-theoretic measures and a new information content measure. New measures of semantic relatedness between ontological concepts are proposed by viewing each concept as a set of its descendent leaf concepts

[1]  Peter D. Karp,et al.  OKBC: A Programmatic Foundation for Knowledge Base Interoperability , 1998, AAAI/IAAI.

[2]  David W. Conrath,et al.  Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy , 1997, ROCLING/IJCLCLP.

[3]  John Murphy,et al.  Using WordNet as a Knowledge Base for Measuring Semantic Similarity between Words , 1994 .

[4]  Philip Resnik,et al.  Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language , 1999, J. Artif. Intell. Res..

[5]  Tony Veale,et al.  An Intrinsic Information Content Metric for Semantic Similarity in WordNet , 2004, ECAI.

[6]  Henry M. Kim,et al.  Predicting how ontologies for the semantic web will evolve , 2002, CACM.

[7]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[8]  Mark A. Musen,et al.  PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment , 2000, AAAI/IAAI.

[9]  Dekang Lin,et al.  An Information-Theoretic Definition of Similarity , 1998, ICML.

[10]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[11]  A. Tversky.  Features of Similarity , 1977 .

[12]  Michael Sussna,et al.  Word sense disambiguation for free-text indexing using a massive semantic network , 1993, CIKM '93.

[13]  Roy Rada,et al.  Development and application of a metric on semantic nets , 1989, IEEE Trans. Syst. Man Cybern..

[14]  Max J. Egenhofer,et al.  Determining Semantic Similarity among Entity Classes from Different Ontologies , 2003, IEEE Trans. Knowl. Data Eng..

[15]  C.J.H. Mann.  Similarity and Compatibility in Fuzzy Set Theory – Assessment and Applications , 2002 .

[16]  Ramanathan V. Guha,et al.  Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project , 1990 .

[17]  Myoung-Ho Kim,et al.  Information Retrieval Based on Conceptual Distance in is-a Hierarchies , 1993, J. Documentation.

[18]  Christiane Fellbaum,et al.  Lexical Chains as Representations of Context for the Detection and Correction of Malapropisms , 1998 .

[19]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[20]  Alexander Budanitsky,et al.  Lexical Semantic Relatedness and Its Application in Natural Language Processing , 1999 .

[21]  P. Resnik.  Selection and information: a class-based approach to lexical relationships , 1993 .

[22]  Norman Y. Foo,et al.  Semantic distance in conceptual graphs , 1992 .

[23]  Graeme Hirst,et al.  Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures , 2004 .