Utilizing local evidence for blog feed search

  • Authors:

  • Yeha Lee;Seung-Hoon Na;Jong-Hyeok Lee

  • Affiliations:

  • Division of Electrical and Computer Engineering, POSTECH, Pohang, South Korea;Department of Computer Science, National University of Singapore, Singapore, Singapore;Division of Electrical and Computer Engineering, POSTECH, Pohang, South Korea

  • Venue:
  • Information Retrieval
  • Year:
  • 2012

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Abstract

Blog feed search aims to identify a blog feed of recurring interest to users on a given topic. A blog feed, the retrieval unit for blog feed search, comprises blog posts of diverse topics. This topical diversity of blog feeds often causes performance deterioration of blog feed search. To alleviate the problem, this paper proposes several approaches based on passage retrieval, widely regarded as effective to handle topical diversity at document level in ad-hoc retrieval. We define the global and local evidence for blog feed search, which correspond to the document-level and passage-level evidence for passage retrieval, respectively, and investigate their influence on blog feed search, in terms of both initial retrieval and pseudo-relevance feedback. For initial retrieval, we propose a retrieval framework to integrate global evidence with local evidence. For pseudo-relevance feedback, we gather feedback information from the local evidence of the top K ranked blog feeds to capture diverse and accurate information related to a given topic. Experimental results show that our approaches using local evidence consistently and significantly outperform traditional ones.