Abstract
The goal of a blog distillation (blog feed search) method is to rank blogs according to their recurrent relevance to the query. An interesting property of blog distillation which differentiates it from traditional retrieval tasks is its dependency on time. In this paper we investigate the effect of time dependency in query expansion. We propose a framework, TEMPER, which selects different terms for different times and ranks blogs according to their relevancy to the query over time. By generating multiple expanded queries based on time, we are able to capture the dynamics of the topic both in aspects and vocabulary usage. We show performance gains over the baseline techniques which generate a single expanded query using the top retrieved posts or blogs irrespective of time.
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Keikha, M., Gerani, S., Crestani, F. (2011). TEMPER: A Temporal Relevance Feedback Method. In: Clough, P., et al. Advances in Information Retrieval. ECIR 2011. Lecture Notes in Computer Science, vol 6611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20161-5_43
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DOI: https://doi.org/10.1007/978-3-642-20161-5_43
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