Overview of YAM++ - (not) Yet Another Matcher for ontology alignment task

Abstract Several challenges to the field of ontology matching have been outlined in recent research. The selection of the appropriate similarity measures as well as the configuration tuning of their combination are known as fundamental issues the community should deal with. Verifying the semantic coherence of the discovered alignment is also known as a crucial task. As the challenging issues are both in basic matching techniques and in their combination, our approach is aimed to provide improvement at the basic matcher level and also at the level of framework. Matching large scale ontologies is currently one of the most challenging issues in ontology matching field. The main reason is that large ontologies are highly heterogeneous both at terminological and conceptual levels. Furthermore, matching very large ontologies entails exploring a very large searching space to discover correspondences. It may also require a huge amount of main memory to maintain the temporary results at each computational step. These factors strongly impact the effectiveness and efficiency of any ontology matching tool. To overcome these issues, we have developed a disk-based ontology matching approach. The underlying idea of our approach is that the complexity and therefore the cost of the matching algorithms are reduced thanks to the indexing data structures by avoiding exhaustive pair-wise comparisons. Indeed, we extensively used indexing techniques in many places. For example, we defined a bitmap encoding the structural information of an ontology. This indexing structure will be exploited for accelerating similarity propagation. Moreover, our approach uses a disk-based mechanism to store temporary data. This allows to perform any ontology matching task on a simple PC or laptop instead of a powerful server. In this paper, we describe YAM++, an ontology matching tool, aimed at solving these issues. We evaluated the efficiency of YAM++ in various OAEI 2012 and OAEI 2013 tracks. YAM++ was one of the best ontology matching systems in terms of F -measure. Most notably, the current version of YAM++ has passed all scalability and large scale ontology matching tests and obtained high matching quality results.

[1]  Fausto Giunchiglia,et al.  S-Match: an Algorithm and an Implementation of Semantic Matching , 2004, ESWS.

[2]  Giovanna Guerrini,et al.  Pushing the limits of OWL 2 reasoners in ontology alignment repair problems , 2016, Intelligenza Artificiale.

[3]  J. Euzenat,et al.  Ontology Matching , 2007, Springer Berlin Heidelberg.

[4]  Enrico Motta,et al.  DSSim Results for OAEI 2008 , 2008, OM.

[5]  Dieter Fensel,et al.  Semantic web portals: state-of-the-art survey , 2005, J. Knowl. Manag..

[6]  Stefan Schlobach,et al.  Debugging and Semantic Clarification by Pinpointing , 2005, ESWC.

[7]  Avigdor Gal,et al.  Advances in Ontology Matching , 2008, Advances in Web Semantics I.

[8]  Erhard Rahm,et al.  Similarity flooding: a versatile graph matching algorithm and its application to schema matching , 2002, Proceedings 18th International Conference on Data Engineering.

[9]  George A. Vouros,et al.  On the discovery of subsumption relations for the alignment of ontologies , 2010, J. Web Semant..

[10]  Kurt Sandkuhl,et al.  A Survey of Exploiting WordNet in Ontology Matching , 2008, IFIP AI.

[11]  Zohra Bellahsene,et al.  A Flexible System for Ontology Matching , 2011, CAiSE Forum.

[12]  Isabel F. Cruz,et al.  Using a layered approach for interoperability on the semantic Web , 2003, Proceedings of the Fourth International Conference on Web Information Systems Engineering, 2003. WISE 2003..

[13]  Yun Peng,et al.  A Bayesian Network Approach to Ontology Mapping , 2005, SEMWEB.

[14]  Cosmin Stroe,et al.  Using AgreementMaker to align ontologies for OAEI 2010 , 2010, OM.

[15]  Angela Maduko,et al.  Using AgreementMaker to align Ontologies for OAEI 2009: Overview, Results, and Outlook , 2009, OM.

[16]  Johanna Völker,et al.  Learning Disjointness for Debugging Mappings between Lightweight Ontologies , 2008, EKAW.

[17]  Cosmin Stroe,et al.  Efficient Selection of Mappings and Automatic Quality-driven Combination of Matching Methods , 2009, OM.

[18]  Fernando Bobillo,et al.  Representation of context-dependant knowledge in ontologies: A model and an application , 2008, Expert Syst. Appl..

[19]  Yuzhong Qu,et al.  Matching large ontologies: A divide-and-conquer approach , 2008, Data Knowl. Eng..

[20]  Ian Horrocks,et al.  Large-scale Interactive Ontology Matching: Algorithms and Implementation , 2012, ECAI.

[21]  V. Svátek,et al.  OntoFarm : Towards an Experimental Collection of Parallel Ontologies , 2005 .

[22]  Watson Wei Khong Chua,et al.  Eff2Match results for OAEI 2010 , 2010, OM.

[23]  Christoph Mangold,et al.  A survey and classification of semantic search approaches , 2007, Int. J. Metadata Semant. Ontologies.

[24]  Gerald Kowalski,et al.  Information Retrieval Systems: Theory and Implementation , 1997 .

[25]  Erhard Rahm,et al.  Generic Schema Matching with Cupid , 2001, VLDB.

[26]  Arie Shoshani,et al.  Optimizing bitmap indices with efficient compression , 2006, TODS.

[27]  Yi Li,et al.  RiMOM: A Dynamic Multistrategy Ontology Alignment Framework , 2009, IEEE Transactions on Knowledge and Data Engineering.

[28]  Steffen Staab,et al.  SEmantic portAL: The SEAL Approach , 2003, Spinning the Semantic Web.

[29]  Jan Nößner,et al.  CODI: Combinatorial Optimization for Data Integration: results for OAEI 2011 , 2010, OM.

[30]  Steffen Staab,et al.  Semantic community Web portals , 2000, Comput. Networks.

[31]  Karim Djouani,et al.  Semantic middleware for context services composition in ubiquitous computing , 2008, MOBILWARE.

[32]  Heiner Stuckenschmidt,et al.  Ontology Alignment Evaluation Initiative: Six Years of Experience , 2011, J. Data Semant..

[33]  Jérôme Euzenat,et al.  Ontology Matching: State of the Art and Future Challenges , 2013, IEEE Transactions on Knowledge and Data Engineering.

[34]  Erhard Rahm,et al.  Rondo: a programming platform for generic model management , 2003, SIGMOD '03.

[35]  Ramanathan V. Guha,et al.  Semantic search , 2003, WWW '03.

[36]  Zohra Bellahsene,et al.  A Generic Approach for Combining Linguistic and Context Profile Metrics in Ontology Matching , 2011, OTM Conferences.

[37]  Bernardo Cuenca Grau,et al.  LogMap 2.0: towards logic-based, scalable and interactive ontology matching , 2011, SWAT4LS.

[38]  Isabel F. Cruz,et al.  AgreementMakerLight results for OAEI 2013 , 2013, OM.

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

[40]  Rajeev Motwani,et al.  Lecture notes on approximation algorithms: Volume I , 1993 .

[41]  Karim Djouani,et al.  Semantic middleware for context services composition in ubiquitous computing , 2008 .

[42]  Chantal Reynaud,et al.  TaxoMap alignment and refinement modules: results for OAEI 2010 , 2010, OM.

[43]  Alessandro Colantonio,et al.  Concise: Compressed 'n' Composable Integer Set , 2010, Inf. Process. Lett..

[44]  Marti A. Hearst.  Automatic Acquisition of Hyponyms from Large Text Corpora , 1992, COLING.

[45]  Masaki Aono,et al.  Anchor-Flood: Results for OAEI 2009 , 2009, OM.

[46]  Pedro M. Domingos,et al.  Ontology Matching: A Machine Learning Approach , 2004, Handbook on Ontologies.

[47]  Zohra Bellahsene,et al.  Opening the Black Box of Ontology Matching , 2013, ESWC.

[48]  Otis Gospodnetic,et al.  Lucene in Action, Second Edition: Covers Apache Lucene 3.0 , 2010 .

[49]  Claude E. Shannon,et al.  Prediction and Entropy of Printed English , 1951 .

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

[51]  Peng Wang.  Lily results on SEALS platform for OAEI 2011 , 2011, OM.

[52]  Guilin Qi,et al.  Combination of Similarity Measures in Ontology Matching Using the OWA Operator , 2011, Recent Developments in the Ordered Weighted Averaging Operators.

[53]  Fabien L. Gandon,et al.  On Ontology Matching Problems , 2004 .

[54]  Mansur R. Kabuka,et al.  ASMOV Results for OAEI 2007 , 2007, OM.

[55]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[56]  S. Lewis,et al.  Uberon, an integrative multi-species anatomy ontology , 2012, Genome Biology.

[57]  Erhard Rahm,et al.  A Clustering-Based Approach for Large-Scale Ontology Matching , 2011, ADBIS.

[58]  Zohra Bellahsene,et al.  Extended Tversky Similarity for Resolving Terminological Heterogeneities across Ontologies , 2013, OTM Conferences.

[59]  A. Halevy.  Why Your Data Won ’ t Mix : Semantic Heterogeneity , 2022 .

[60]  Jérôme Euzenat,et al.  Ten Challenges for Ontology Matching , 2008, OTM Conferences.

[61]  Erhard Rahm,et al.  Schema and ontology matching with COMA++ , 2005, SIGMOD '05.

[62]  Pradeep Ravikumar,et al.  A Comparison of String Distance Metrics for Name-Matching Tasks , 2003, IIWeb.

[63]  Steffen Staab,et al.  QOM - Quick Ontology Mapping , 2004, GI Jahrestagung.

[64]  Mark A. Musen,et al.  Anchor-PROMPT: Using Non-Local Context for Semantic Matching , 2001, OIS@IJCAI.

[65]  Ricardo de Almeida Falbo,et al.  Using Ontologies to Add Semantics to a Software Engineering Environment , 2005, SEKE.

[66]  Olivier Bodenreider,et al.  The Unified Medical Language System (UMLS): integrating biomedical terminology , 2004, Nucleic Acids Res..

[67]  Emanuel Santos,et al.  Ontology Alignment Repair through Modularization and Confidence-Based Heuristics , 2013, PloS one.

[68]  Paul R. Smart,et al.  An Analysis of the Origin of Ontology Mismatches on the Semantic Web , 2008, EKAW.

[69]  Jérôme Euzenat,et al.  Ontology Alignment with OLA , 2004, EON.

[70]  Erhard Rahm,et al.  GOMMA results for OAEI 2012 , 2012, OM.

[71]  Anuj R. Jaiswal,et al.  OMEN: A Probabilistic Ontology Mapping Tool , 2005, SEMWEB.

[72]  Bernardo Cuenca Grau,et al.  LogMap: Logic-Based and Scalable Ontology Matching , 2011, SEMWEB.

[73]  Natalya F. Noy,et al.  Semantic integration: a survey of ontology-based approaches , 2004, SGMD.

[74]  Ming Mao,et al.  An adaptive ontology mapping approach with neural network based constraint satisfaction , 2010, J. Web Semant..

[75]  Gayo Diallo,et al.  An effective method of large scale ontology , 2014 .

[76]  Fabien L. Gandon,et al.  On Ontology Matching Problems - for Building a Corporate Semantic Web in a Multi-Communities Organization , 2004, ICEIS.

[77]  Yuzhong Qu,et al.  ObjectCoref & Falcon-AO: results for OAEI 2010 , 2010, OM.

[78]  Christian Meilicke,et al.  Alignment incoherence in ontology matching , 2011 .

[79]  Zohra Bellahsene,et al.  YAM++ results for OAEI 2011 , 2011, OM.

[80]  Wolfram Wöß,et al.  A Semantic Web middleware for Virtual Data Integration on the Web , 2008, ESWC.

[81]  Zohra Bellahsene,et al.  Efficient Semantic Verification of Ontology Alignment , 2015, 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT).

[82]  Velma L. Payne,et al.  Hospital care watch (HCW): an ontology and rule-based intelligent patient management assistant , 2005, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05).

[83]  Michel Klein,et al.  Combining and relating ontologies: an analysis of problems and solutions , 2001, OIS@IJCAI.