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Communication Dans Un Congrès Année : 2012

GTE: A Distributional Second-Order Co-Occurrence Approach to Improve the Identification of Top Relevant Dates in Web Snippets

Résumé

In this paper, we present an approach to identify top relevant dates in Web snippets with respect to a given implicit temporal query. Our approach is two-fold. First, we propose a generic temporal similarity measure called GTE, which evaluates the temporal similarity between a query and a date. Second, we propose a classification model to accurately relate relevant dates to their corresponding query terms and withdraw irrelevant ones. We suggest two different solutions: a threshold-based classification strategy and a supervised classifier based on a combination of multiple similarity measures. We evaluate both strategies over a set of real-world text queries and compare the performance of our Web snippet approach with a query log approach over the same set of queries. Experiments show that determining the most relevant dates of any given implicit temporal query can be improved with GTE combined with the second order similarity measure InfoSimba, the Dice coefficient and the threshold-based strategy compared to (1) first-order similarity measures and (2) the query log based approach.
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Dates et versions

hal-01070926 , version 1 (09-10-2014)

Identifiants

Citer

Ricardo Campos, Gaël Dias, Mário Jorge Alípio, Célia Nunes. GTE: A Distributional Second-Order Co-Occurrence Approach to Improve the Identification of Top Relevant Dates in Web Snippets. 21st ACM international conference on Information and knowledge management (CIKM), Oct 2012, sheraton, mai hawaii, United States. pp.Pages 2035-2039, ⟨10.1145/2396761.2398567⟩. ⟨hal-01070926⟩
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