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Refreshing Models to Provide Timely Query Recommendations

10 years 12 months ago
Refreshing Models to Provide Timely Query Recommendations
In this work we propose a comparative study of the effects of a continuous model update on the effectiveness of wellknown query recommendation algorithms. In their original formulation, these algorithms use static (i.e. pre-computed) models to generate recommendations. We extend these algorithms to generate suggestions using: a static model (no updates), a model updated periodically, and a model continuously updating (i.e. each time a query is submitted). We assess the results by previously proposed evaluation metrics and we show that the use of periodical and continuous updates of the model used for recommending queries provides better recommendations.
Daniele Broccolo, Franco Maria Nardini, Raffaele P
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where IIR
Authors Daniele Broccolo, Franco Maria Nardini, Raffaele Perego, Fabrizio Silvestri
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