Mining query log graphs towards a query folksonomy
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE(2012)
摘要
The human interaction through the web generates both implicit and explicit knowledge. An example of an implicit contribution is searching, as people contribute with their knowledge by clicking on retrieved documents. When this information is available, an important and interesting challenge is to extract relations from query logs, and, in particular, semantic relations between queries and their terms. In this paper, we present and discuss results on query contextualization through the association of tags to queries, that is, query folksonomies. Note that tags may not even occur within the query. Our results rely on the analysis of large query log induced graphs, namely click induced graphs. Results obtained with real data show that the inferred query folksonomy provide interesting insights both on semantic relations among queries and on web users intent.Copyright © 2011 John Wiley & Sons, Ltd. (Work done while visiting Yahoo! Research Barcelona.)
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关键词
large query log,implicit contribution,mining query log graph,interesting insight,explicit knowledge,query log,query contextualization,induced graph,interesting challenge,query folksonomy,query folksonomies,semantic relation
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