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Journal Article

Semantic Similarity Search on Semistructured Data with the XXL Search Engine

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45380

Schenkel,  Ralf
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45608

Theobald,  Anja
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Schenkel, R., Theobald, A., & Weikum, G. (2005). Semantic Similarity Search on Semistructured Data with the XXL Search Engine. Information Retrieval, 8, 521-545.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-27A5-F
Abstract
Query languages for XML such as XPath or XQuery support Boolean retrieval: a query result is a (possibly restructured) subset of XML elements or entire documents that satisfy the search conditions of the query. This search paradigm works for highly schematic XML data collections such as electronic catalogs. However, for searching information in open environments such as the Web or intranets of large corporations, ranked retrieval is more appropriate: a query result is a ranked list of XML elements in descending order of (estimated) relevance. Web search engines, which are based on the ranked retrieval paradigmdo, however, not consider the additional information and rich annotations provided by the structure of XML documents and their element names. This article presents the XXL search engine that supports relevance ranking on XML data. XXL is particularly geared for path queries with wildcards that can span multiple XML collections and contain both exact-match as well as semantic-similarity search conditions. In addition, ontological information and suitable index structures are used to improve the search efficiency and effectiveness. XXL is fully implemented as a suite of Java classes and servlets. Experiments in the context of the INEX benchmark demonstrate the efficiency of the XXL search engine and underline its effectiveness for ranked retrieval.