A novel automatic property weight generator for semantic data integration

The dramatic increase of heterogeneous data resources, whether they are semantic knowledge bases or databases, demands for an automatic data integration technique, which is directly affected by the weight of property associated to instances or data. Choosing a suitable metric for generating weight for a property automatically is nevertheless a formidable task. In this study, we analyze different metrics for generating weights and formulate mathematical reasoning to select an appropriate one. Our observation suggests that the weight of a property is highly influenced by the number of instances contain the property, the number of instances contain the distinct value for the property and the total number of instances in a training dataset. The experiments and evaluations illustrate the fact and shows the strength of automatic weight generator for properties in a data integration technique.

[1]  Howard B. Newcombe,et al.  Handbook of record linkage: methods for health and statistical studies, administration, and business , 1988 .

[2]  William E. Winkler,et al.  The State of Record Linkage and Current Research Problems , 1999 .

[3]  P. Ivax,et al.  A THEORY FOR RECORD LINKAGE , 2004 .

[4]  Heiner Stuckenschmidt,et al.  Results of the Ontology Alignment Evaluation Initiative 2007 , 2006, OM.

[5]  Heiner Stuckenschmidt,et al.  Results of the Ontology Alignment Evaluation Initiative , 2007 .

[6]  Silvana Castano,et al.  Instance Matching for Ontology Population , 2008, SEBD.

[7]  Mansur R. Kabuka,et al.  ASMOV: results for OAEI 2010 , 2010, OM.

[8]  Jan Hidders,et al.  SERIMI - resource description similarity, RDF instance matching and interlinking , 2011, OM.

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

[10]  Masaki Aono,et al.  Augmentation of ontology instance matching by automatic weight generation , 2011, 2011 World Congress on Information and Communication Technologies.

[11]  Masaki Aono,et al.  Resolving scalability issue to ontology instance matching in Semantic Web , 2012, 2012 15th International Conference on Computer and Information Technology (ICCIT).

[12]  S. Handschuh,et al.  Discovering Semantic Equivalence of People behind Online Profiles , 2012 .

[13]  Masaki Aono,et al.  An Efficient Method for Ontology Instance Matching , 2012 .

[14]  Yue Zhao,et al.  RiMOM results for OAEI 2016 , 2010, OM@ISWC.