Abstract
Semantic Web data seems like a promising source of information for improving search. While there is some literature about how semantic data should be used to enhance search, there are no positive conclusions about the best approach. This paper surveys existing approaches to semantic web search, describes adapting a TREC benchmark for evaluation, and proposes a learned representation algorithm for using semantic web data in search. © Springer-Verlag Berlin Heidelberg 2009.
Cite
CITATION STYLE
Gronski, J. (2009). Semantic Web for search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5823 LNCS, pp. 957–964). Springer Verlag. https://doi.org/10.1007/978-3-642-04930-9_61
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