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| Content Provider | Springer Nature Link |
|---|---|
| Author | Roos, Nico Schadd, Frederik C. |
| Copyright Year | 2014 |
| Abstract | Ontology mapping is a crucial task for the facilitation of information exchange and data integration. A mapping system can use a variety of similarity measures to determine concept correspondences. This paper proposes the integration of word-sense disambiguation techniques into lexical similarity measures. We propose a disambiguation methodology which entails the creation of virtual documents from concept and sense definitions, including their neighbourhoods. The specific terms are weighted according to their origin within their respective ontology. The document similarities between the concept document and sense documents are used to disambiguate the concept meanings. First, we evaluate to what extent the proposed disambiguation method can improve the performance of a lexical similarity metric. We observe that the disambiguation method improves the performance of each tested lexical similarity metric. Next, we demonstrate the potential of a mapping system utilizing the proposed approach through the comparison with contemporary ontology mapping systems. We observe a high performance on a real-world data set. Finally, we evaluate how the application of several term-weighting techniques on the virtual documents can affect the quality of the generated alignments. Here, we observe that weighting terms according to their ontology origin leads to the highest performance. |
| Starting Page | 167 |
| Ending Page | 186 |
| Page Count | 20 |
| File Format | |
| ISSN | 18612032 |
| Journal | Journal on Data Semantics |
| Volume Number | 4 |
| Issue Number | 3 |
| e-ISSN | 18612040 |
| Language | English |
| Publisher | Springer Berlin Heidelberg |
| Publisher Date | 2014-09-30 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | Subscribed |
| Subject Keyword | Semantic web Virtual document Ontology mapping Word-sense disambiguation Lexical similarity Database Management Information Storage and Retrieval Artificial Intelligence (incl. Robotics) Information Systems Applications (incl. Internet) IT in Business |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Computer Networks and Communications Information Systems |
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