Disambiguating Implicit Temporal Queries by Clustering Top Relevant Dates in Web Snippets
Disambiguating Implicit Temporal Queries by Clustering Top Relevant Dates in Web Snippets
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Date
2012
Authors
Ricardo Campos
Alípio Jorge
Célia Nunes
Gaël Dias
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Abstract
With the growing popularity of research in Temporal
Information Retrieval (T-IR), a large amount of temporal data is
ready to be exploited. The ability to exploit this information can
be potentially useful for several tasks. For example, when
querying 'Football World Cup Germany', it would be
interesting to have two separate clusters {1974, 2006}
corresponding to each of the two temporal instances. However,
clustering of search results by time is a non-trivial task that
involves determining the most relevant dates associated to a
query. In this paper, we propose a first approach to flat temporal
clustering of search results. We rely on a second order cooccurrence
similarity measure approach which first identifies
top relevant dates. Documents are grouped at the year level,
forming the temporal instances of the query. Experimental tests
were performed using real-world text queries. We used several
measures for evaluating the performance of the system and
compared our approach with Carro