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The Sesame Lucene Sail: RDF Queries with Full-text Search

by: Enrico Minack, Leo Sauermann, Gunnar Grimnes, Christiaan Fluit, and Jeen Broekstra

, Nr. 2008-1 (February 2008) .

Resources (URL, PDF, PS...)

URL:	http://nepomuk.semanticdesktop.org/xwiki/bin/download/Main1/Publications/Minack%202008.pdf

With the growth of the Semantic Web, the requirements on storing and querying RDF has become more sophisticated. When a larger amount of data has to be managed, queries in structured query languages, such as SPARQL, are not always powerful enough. Use of additional keywords for querying can further reduce the result set towards the actual relevant answers, however, SPARQL only provides complete string matching or filtering based on regular expressions, which is a very slow operation. In contrast, state of the art Information Retrieval IR techniques provide sophisticated features such as keyword search, lemmatisation, stemming and ranking. In this paper we present a combination of structured RDF queries and full-text search. It is implemented as an extension of an established RDF store Sesame with IR capabilities using the text search library Lucene, without requiring modifications to existing RDF query languages.

BibTeX record

@techreport{Minack+2008,
  abstract = {With the growth of the Semantic Web, the requirements on storing and querying RDF has become more sophisticated. When a larger amount of data has to be managed, queries in structured query languages, such as SPARQL, are not always powerful enough. Use of additional keywords for querying can further reduce the result set towards the actual relevant answers, however, SPARQL only provides complete string matching or filtering based on regular expressions, which is a very slow operation. In contrast, state of the art Information Retrieval (IR) techniques provide sophisticated features such as keyword search, lemmatisation, stemming and ranking. In this paper we present a combination of structured RDF queries and full-text search. It is implemented as an extension of an established RDF store (Sesame) with IR capabilities using the text search library Lucene, without requiring modifications to existing RDF query languages.
},
  added-at = {2008-02-14T13:50:10.000+0100},
  author = {Minack, Enrico and Sauermann, Leo and Grimnes, Gunnar and Fluit, Christiaan and Broekstra, Jeen},
  biburl = {http://www.bibsonomy.org/bibtex/2a87a7c940a5236a9bba3e9e258660690/nepomuk},
  institution = {NEPOMUK Consortium},
  interhash = {a7fa25ef725ca2019f66334ec5ded94b},
  intrahash = {a87a7c940a5236a9bba3e9e258660690},
  keywords = {02 2008 aduna dfki from:leobard imported l3s lang:en nepomuk wp2},
  month = {February},
  number = {2008-1},
  owner = {sauermann},
  pdf = {Minack+2008.pdf},
  timestamp = {2008-02-14T13:50:10.000+0100},
  title = {The Sesame Lucene Sail: RDF Queries with Full-text Search},
  type = {Technical Report},
  url = {http://nepomuk.semanticdesktop.org/xwiki/bin/download/Main1/Publications/Minack%202008.pdf},
  year = 2008
}

Endnote record

%0 Report
%1 Minack+2008
%A Minack, Enrico
%A Sauermann, Leo
%A Grimnes, Gunnar
%A Fluit, Christiaan
%A Broekstra, Jeen
%D 2008
%K 
%N 2008-1
%T The Sesame Lucene Sail: RDF Queries with Full-text Search
%U http://nepomuk.semanticdesktop.org/xwiki/bin/download/Main1/Publications/Minack%202008.pdf
%X With the growth of the Semantic Web, the requirements on storing and querying RDF has become more sophisticated. When a larger amount of data has to be managed, queries in structured query languages, such as SPARQL, are not always powerful enough. Use of additional keywords for querying can further reduce the result set towards the actual relevant answers, however, SPARQL only provides complete string matching or filtering based on regular expressions, which is a very slow operation. In contrast, state of the art Information Retrieval (IR) techniques provide sophisticated features such as keyword search, lemmatisation, stemming and ranking. In this paper we present a combination of structured RDF queries and full-text search. It is implemented as an extension of an established RDF store (Sesame) with IR capabilities using the text search library Lucene, without requiring modifications to existing RDF query languages.

BibSonomy :: publication ::

The Sesame Lucene Sail: RDF Queries with Full-text Search

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Abstract

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Endnote record