Abstract
The goal of ontology matching is to find relations between entities expressed in different ontologies. Very often, these relations are equivalence relations that are discovered through the measure of similarity between these entities. However, more elaborate methods may directly find more precise relations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
References
Araújo, S., Tran, D., DeVries, A., Hidders, J., Schwabe, D.: SERIMI: class-based disambiguation for effective instance matching over heterogeneous web data. In: Proc. 15th International Workshop on the Web and Databases (WebDB) at the International Conference on Management of Data (SIGMOD), Scottsdale, AZ, USA, pp. 25–30 (2012)
Atencia, M., David, J., Scharffe, F.: Keys and pseudo-keys detection for web datasets cleansing and interlinking. In: Proc. 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW), Galway, Ireland. Lecture Notes in Computer Science, vol. 7603, pp. 144–153 (2012b)
Biron, P., Malhotra, A. (eds.): XML schema part 2: Datatypes. Recommendation, W3C (2004). http://www.w3.org/TR/xpath
Bourigault, D., Jacquemin, C.: Term extraction + term clustering: an integrated platform for computer-aided terminology. In: Proc. European Chapter of the Association for Computational Linguistics (EACL), Bergen, Norway, pp. 15–22 (1999)
Brill, E.: A simple rule-based part of speech tagger. In: Proc. 3rd Conference on Applied Natural Language Processing (ANLC), Trento, Italy, pp. 152–155 (1992)
Budanitsky, A., Hirst, G.: Evaluating WordNet-based measures of lexical semantic relatedness. Comput. Linguist. 32(1), 13–47 (2006)
Cerbah, F., Euzenat, J.: Traceability between models and texts through terminology. Data Knowl. Eng. 38(1), 31–43 (2001)
Cohen, W., Ravikumar, P., Fienberg, S.: A comparison of string metrics for matching names and records. In: Proc. International Workshop on Data Cleaning and Object Consolidation at the 9th International Conference on Knowledge Discovery and Data Mining (KDD), Washington, DC, USA (2003b)
Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V., Aswani, N., Roberts, I., Gorrell, G., Funk, A., Roberts, A., Damljanovic, D., Heitz, T., Greenwood, M., Saggion, H., Petrak, J., Li, Y., Peters, W.: Text Processing with GATE (Version 6). University of Sheffield, Sheffield (2011)
Damerau, F.: A technique for computer detection and selection of spelling errors. Commun. ACM 7(3), 171–176 (1964)
Deerwester, S., Dumais, S., Furnas, G., Landauer, T., Harshman, R.: Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci. 41(6), 391–407 (1990)
Ehrig, M., Sure, Y.: Ontology mapping—an integrated approach. In: Proc. 1st European Semantic Web Symposium (ESWS), Hersounisous, Greece. Lecture Notes in Computer Science, vol. 3053, pp. 76–91 (2004)
Elfeky, M., Elmagarmid, A., Verykios, V.: TAILOR: a record linkage tool box. In: Proc. 18th International Conference on Data Engineering (ICDE), San Jose, CA, USA, pp. 17–28 (2002)
Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-lite. In: Proc. 16th European Conference on Artificial Intelligence (ECAI), Valencia, Spain, pp. 333–337 (2004)
Euzenat, J., Bach, T.L., Barrasa, J., Bouquet, P., De Bo, J., Dieng-Kuntz, R., Ehrig, M., Hauswirth, M., Jarrar, M., Lara, R., Maynard, D., Napoli, A., Stamou, G., Stuckenschmidt, H., Shvaiko, P., Tessaris, S., Van Acker, S., Zaihrayeu, I.: State of the art on ontology alignment. Deliverable D2.2.3, Knowledge web NoE (2004)
Fellbaum, C.: WordNet: an Electronic Lexical Database. MIT Press, Cambridge (1998)
Fellegi, I., Sunter, A.: A theory for record linkage. J. Am. Stat. Assoc. 64(328), 1183–1210 (1969)
Ferrara, A., Nikolov, A., Scharffe, F.: Data linking for the semantic web. Int. J. Semantic Web Inf. Syst. 7(3), 46–76 (2011b)
Fu, B., Brennan, R., O’Sullivan, D.: A configurable translation-based cross-lingual ontology mapping system to adjust mapping outcomes. J. Web Semant. 15, 15–36 (2012)
Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, Berlin (1999)
Giunchiglia, F., Yatskevich, M.: Element level semantic matching. In: Proc. International Workshop on Meaning Coordination and Negotiation at the 3rd International Semantic Web Conference (ISWC), Hiroshima, Japan, pp. 37–48 (2004)
Giunchiglia, F., Shvaiko, P., Yatskevich, M.: S-Match: an algorithm and an implementation of semantic matching. In: Proc. 1st European Semantic Web Symposium (ESWS), Hersounisous, Greece. Lecture Notes in Computer Science, vol. 3053, pp. 61–75 (2004)
Giunchiglia, F., Shvaiko, P., Yatskevich, M.: Discovering missing background knowledge in ontology matching. In: Proc. 17th European Conference on Artificial Intelligence (ECAI), Riva del Garda, Italy, pp. 382–386 (2006c)
Gotoh, O.: An improved algorithm for matching biological sequences. J. Mol. Biol. 162(3), 705–708 (1981)
Gracia, J.: Integration and disambiguation techniques for semantic heterogeneity reduction on the web. PhD thesis, Universidad de Zaragoza, Zaragoza, Spain (2009)
Hamming, R.: Error detecting and error correcting codes. Technical Report 2. Bell Syst. Tech. J. (1950)
Hausdorff, F.: Grundzüge der Mengenlehre, p. 476. Verlag Veit, Leipzig (1914)
Ide, N., Véronis, J.: Word Sense Disambiguation: the state of the art. Comput. Linguist. 24(1), 1–40 (1998)
Isele, R., Bizer, C.: Active learning of expressive linkage rules using genetic programming. J. Web Semant. (2013, in press)
Jaccard, P.: Distribution de la flore alpine dans le bassin des Dranses et dans quelques régions voisines. Bull. Soc. Vaud. Sci. Nat. 37, 241–272 (1901)
Jacquemin, C., Tzoukermann, E.: NLP for term variant extraction: synergy between morphology, lexicon and syntax. In: Strzalkowski, T. (ed.) Language Information Retrieval, pp. 25–74. Kluwer, Boston (1999)
Jaro, M.: UNIMATCH: A record linkage system: User’s manual. Technical report, U.S. Bureau of the Census, Washington, DC, USA (1976)
Jaro, M.: Advances in record-linkage methodology as applied to matching the 1985 census of Tampa, Florida. J. Am. Stat. Assoc. 84(406), 414–420 (1989)
Jiang, J., Conrath, D.: Semantic similarity based on corpus statistics and lexical taxonomy. In: Proc. 10th International Conference on Research in Computational Linguistics (ROCLING), Taipei, Taiwan, pp. 19–33 (1997)
Jung, J., Håkansson, A., Hartung, R.: Indirect alignment between multilingual ontologies: a case study of Korean and Swedish ontologies. In: Proc. 3rd Symposium on Agents and Multi-agent Systems: Technologies and Applications (KES-AMSTA), Uppsala, Sweden. Lecture Notes in Computer Science, vol. 5559, pp. 233–241 (2009)
Köpcke, H., Rahm, E.: Frameworks for entity matching: a comparison. Data Knowl. Eng. 69(2), 197–210 (2010)
Kullback, S., Leibler, R.: On information and sufficiency. Ann. Math. Stat. 22(79), 498–519 (1951)
Larson, J., Navathe, S., Elmasri, R.: A theory of attributed equivalence in databases with application to schema integration. IEEE Trans. Softw. Eng. 15(4), 449–463 (1989)
Lee, M.L., Yang, L.H., Hsu, W., Yang, X.: XClust: clustering XML schemas for effective integration. In: Proc. 11th International Conference on Information and Knowledge Management (CIKM), McLean, VA, USA, pp. 292–299 (2002)
Lesk, M.: Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. In: Proc. 5th Annual International Conference on Systems Documentation (SIGDOC), Toronto, Canada, pp. 24–26 (1986)
Levenshtein, V.: Binary codes capable of correcting deletions, insertions, and reversals. Dokl. Akad. Nauk SSSR 163(4), 845–848 (1965). In Russian. English translation in Sov. Phys. Dokl. 10(8), 707–710 (1966)
Li, W.-S., Clifton, C.: Semantic integration in heterogeneous databases using neural networks. In: Proc. 20th International Conference on Very Large Data Bases (VLDB), Santiago, Chile, pp. 1–12 (1994)
Lim, E.-P., Srivastava, J., Prabhakar, S., Richardson, J.: Entity identification in database integration. In: Proc. 9th International Conference on Data Engineering (ICDE), Vienna, Austria, pp. 294–301 (1993)
Lin, D.: An information-theoretic definition of similarity. In: Proc. 15th International Conference of Machine Learning (ICML), Madison, WI, USA, pp. 296–304 (1998)
Lovins, J.B.: Development of a stemming algorithm. Mech. Transl. Comput. Linguist. 11(1), 22–31 (1968)
Maynard, D.: Term recognition using combined knowledge sources. PhD thesis, Manchester Metropolitan University, Manchester, UK (1999)
Maynard, D., Ananiadou, S.: Term extraction using a similarity-based approach. In: Bourigault, D., Jacquemin, C., Lhomme, M.-C. (eds.) Recent Advances in Computational Terminology, pp. 261–278. Benjamins, Amsterdam (2001)
McCandless, M., Hatcher, E., Gospodnetić, O.: Lucene in Action, 2nd edn. Manning Publications, Shelter Island (2010)
Miller, G.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)
Monge, A., Elkan, C.: An efficient domain-independent algorithm for detecting approximately duplicate database records. In: Proc. International Workshop on Data Mining and Knowledge Discovery at the 16th International Conference on Management of Data (SIGMOD), Tucson, AZ, USA (1997)
Navathe, S., Buneman, P.: Integrating user views in database design. Computer 19(1), 50–62 (1986)
Needleman, S., Wunsch, C.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48(3), 443–453 (1970)
Ngomo, A.-C.N.: A time-efficient hybrid approach to link discovery. In: Proc. 6th International Workshop on Ontology Matching (OM) at the 10th International Semantic Web Conference (ISWC), Bonn, Germany, pp. 1–12 (2011)
Ngomo, A.-C.N., Auer, S.: LIMES: a time-efficient approach for large-scale link discovery on the web of data. In: Proc. 22nd International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Spain, pp. 2312–2317 (2011)
Nikolov, A., Uren, V., Motta, E., de Roeck, A.: Overcoming schema heterogeneity between linked semantic repositories to improve coreference resolution. In: Proc. 4th Asian Semantic Web Conference (ASWC), Bangkok, Thailand. Lecture Notes in Computer Science, vol. 5367, pp. 332–346 (2009)
Pedersen, T., Patwardhan, S., Michelizzi, J.: WordNet::Similarity—measuring the relatedness of concepts. In: Proc. 19th National Conference on Artificial Intelligence (AAAI), San Jose, CA, USA, pp. 1024–1025 (2004)
Porter, M.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)
Qu, Y., Hu, W., Chen, G.: Constructing virtual documents for ontology matching. In: Proc. 15th International World Wide Web Conference (WWW), Edinburgh, UK, pp. 23–31 (2006)
Rahm, E., Bernstein, P.: A survey of approaches to automatic schema matching. VLDB J. 10(4), 334–350 (2001)
Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. In: Proc. 14th International Joint Conference on Artificial Intelligence (IJCAI), Montréal, Canada, pp. 448–453 (1995)
Resnik, P.: Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. J. Artif. Intell. Res. 11, 95–130 (1999)
Robertson, S., Spärck Jones, K.: Relevance weighting of search terms. J. Am. Soc. Inf. Sci. 27(3), 129–146 (1976)
Saint-Onge, D.: Detecting and correcting malapropisms with lexical chains. Master’s thesis, University of Toronto, Toronto, Canada (1995)
Salton, G.: The SMART Retrieval System: Experiments in Automatic Information Processing. Prentice Hall, Englewood Cliffs (1971)
Salton, G., McGill, M.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
Scharffe, F., Euzenat, J.: Linked data meets ontology matching: enhancing data linking through ontology alignments. In: Proc. 3rd International Conference on Knowledge Engineering and Ontology Development (KEOD), Paris, France, pp. 279–284 (2011)
Sheth, A., Larson, J., Cornelio, A., Navathe, S.: A tool for integrating conceptual schemas and user views. In: Proc. 4th International Conference on Data Engineering (ICDE), Los Angeles, CA, USA, pp. 176–183 (1988)
Smith, T., Waterman, M.: Identification of common molecular subsequences. J. Mol. Biol. 147(1), 195–197 (1981)
Spohr, D., Hollink, L., Cimiano, P.: A machine learning approach to multilingual and cross-lingual ontology matching. In: Proc. 10th International Semantic Web Conference (ISWC), Bonn, Germany. Lecture Notes in Computer Science, vol. 7031, pp. 665–680 (2011)
Stoilos, G., Stamou, G., Kollias, S.: A string metric for ontology alignment. In: Proc. 4th International Semantic Web Conference (ISWC), Galway, Ireland. Lecture Notes in Computer Science, vol. 3729, pp. 624–637 (2005)
Trojahn, C., Quaresma, P., Vieira, R.: An API for multilingual ontology matching. In: Proc. 7th Language Resources and Evaluation Conference (LREC), Valletta, Malta, pp. 3830–3835 (2010b)
Tverski, A.: Features of similarity. Psychol. Rev. 84(2), 327–352 (1977)
Valtchev, P.: Construction automatique de taxonomies pour l’aide à la représentation de connaissances par objets. Thèse d’informatique, Université Grenoble 1, Grenoble, France (1999)
Valtchev, P., Euzenat, J.: Dissimilarity measure for collections of objects and values. In: Proc. 2nd Symposium on Intelligent Data Analysis (IDA), London, UK. Lecture Notes in Computer Science, vol. 1280, pp. 259–272 (1997)
Winkler, W.: The state of record linkage and current research problems. Technical Report 99/04, Statistics of Income Division, Internal Revenue Service Publication (1999)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Euzenat, J., Shvaiko, P. (2013). Basic Similarity Measures. In: Ontology Matching. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38721-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-38721-0_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38720-3
Online ISBN: 978-3-642-38721-0
eBook Packages: Computer ScienceComputer Science (R0)