Paper Info
Title
GTE: a distributional second-order co-occurrence approach to improve the identification of top relevant dates in web snippets
Abstract
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.
Year
DOI
Venue
2012
10.1145/2396761.2398567
CIKM
Keywords
Field
DocType
corresponding query term,implicit temporal query,web snippet,query log,first-order similarity measure,distributional second-order co-occurrence approach,multiple similarity measure,web snippet approach,top relevant date,relevant date,real-world text query,query log approach,generic temporal similarity measure
Query optimization,Data mining,Web search query,Similarity measure,Query expansion,Information retrieval,Computer science,Sargable,Web query classification,Classifier (linguistics),Snippet
Conference
Citations 
PageRank 
References 
12
0.71
10
Authors
4
Name
Order
Citations
PageRank
Ricardo Campos1447.35
Gaël Dias235441.95
Alípio Jorge374973.03
Celia Nunes4456.29