Resolving XML semantic ambiguity
XML semantic-aware processing has become a motivating and important challenge in Web data management, data processing, and information retrieval. While XML data is semi-structured, yet it remains prone to lexical ambiguity, and thus requires dedicated semantic analysis and sense disambiguation proce...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| التنسيق: | conferenceObject |
| منشور في: |
2015
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/5873 http://dx.doi.org/10.5441/002/edbt.2015.25 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://univ-pau.hal.science/hal-01909107/ |
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| الملخص: | XML semantic-aware processing has become a motivating and important challenge in Web data management, data processing, and information retrieval. While XML data is semi-structured, yet it remains prone to lexical ambiguity, and thus requires dedicated semantic analysis and sense disambiguation processes to assign well-defined meaning to XML elements and attributes. This becomes crucial in an array of applications ranging over semantic-aware query rewriting, semantic document clustering and classification, schema matching, as well as blog analysis and event detection in social networks and tweets. Most existing approaches in this context: i) ignore the problem of identifying ambiguous XML nodes, ii) only partially consider their structural relations/context, iii) use syntactic information in processing XML data regardless of the semantics involved, and iv) are static in adopting fixed disambiguation constraints thus limiting user involvement. In this paper, we provide a new XML Semantic Disambiguation Framework titled XSDF designed to address each of the above motivations, taking as input: an XML document and a general purpose semantic network, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts. Experiments demonstrate the effectiveness of our approach in comparison with alternative methods. |
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