A novel asymmetric semantic similarity measurement for semantic job matching

Applying semantic similarity techniques in semantic matching applications can help to match information not only lexically but also semantically. In this paper, we extend the conventional semantic similarity measures for retrieving and ranking employment candidates in the case of semantic job matching. A framework for calculating asymmetric conceptual skill similarity is proposed, and validated in a use case of programming job matching. Within this case, a specific skills taxonomy has been formalized in Simple Knowledge Organization System (SKOS). A novel asymmetric semantic similarity measurement based on weighted-path-counting is proposed and validated in the use case. The proposed algorithms are evaluated by comparing them to user ranks, and our experimental results show that the proposed algorithms have better performance in ranking comparing to the conventional algorithms.

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

[2]  Yin Guisheng,et al.  Research on Ontology-Based Measuring Semantic Similarity , 2008, 2008 International Conference on Internet Computing in Science and Engineering.

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

[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]  Zhenyu He,et al.  Robust Object Tracking via Key Patch Sparse Representation , 2017, IEEE Transactions on Cybernetics.

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

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

[8]  Christiane Fellbaum,et al.  Combining Local Context and Wordnet Similarity for Word Sense Identification , 1998 .

[9]  Euripides G. M. Petrakis,et al.  X-Similarity: Computing Semantic Similarity between Concepts from Different Ontologies , 2006, J. Digit. Inf. Manag..

[10]  Mark S. Fox,et al.  Semantic Matchmaking for Job Recruitment: An Ontology-Based Hybrid Approach , 2009 .

[11]  Shaha T. Al-Otaibi,et al.  A survey of job recommender systems , 2012 .

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

[13]  Yong Yu,et al.  Conceptual Graph Matching for Semantic Search , 2002, ICCS.

[14]  Xiaoping Yang,et al.  WNOntoSim: A Hybrid Approach for Measuring Semantic Similarity between Ontologies Based on WordNet , 2011, 2011 Eighth Web Information Systems and Applications Conference.

[15]  Zhenyu He,et al.  Connected Component Model for Multi-Object Tracking , 2016, IEEE Transactions on Image Processing.

[16]  Huajun Chen,et al.  Linked data based semantic similarity and data mining , 2010, 2010 IEEE International Conference on Information Reuse & Integration.

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

[18]  David Sánchez,et al.  Ontology-based semantic similarity: A new feature-based approach , 2012, Expert Syst. Appl..

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

[20]  David McLean,et al.  An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources , 2003, IEEE Trans. Knowl. Data Eng..

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

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

[23]  Marek Reformat,et al.  Feature-based similarity assessment in ontology using fuzzy set theory , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[24]  Jérôme Euzenat,et al.  A Feature and Information Theoretic Framework for Semantic Similarity and Relatedness , 2010, SEMWEB.

[25]  Troels Andreasen,et al.  On Measuring Similarity for Conceptual Querying , 2002, FQAS.