Utilizing local evidence for blog feed search

• Published in: Information retrieval (Boston) Vol. 15; no. 2; pp. 157 - 177
• Main Authors: Lee, Yeha, Na, Seung-Hoon, Lee, Jong-Hyeok
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.04.2012; Springer; Springer Nature B.V
• Subjects: Blogs; Computer Science; Data Mining and Knowledge Discovery; Data Structures and Information Theory; Deterioration; Documents; Exact sciences and technology; Feedback; Handles; Information and communication sciences; Information processing and retrieval; Information retrieval; Information retrieval systems. Information and document management system; Information retrieval. Man machine relationship; Information science. Documentation; Information Storage and Retrieval; Natural Language Processing (NLP); Pattern Recognition; Performance degradation; Performance evaluation; Product reviews; Query expansion; Retrieval; Sciences and techniques of general use; Search engines; Searching; Studies; South Korea; Pseudo-relevance feedback; Blog distillation; Blog feed search; Passage-based retrieval; Word; User; Diversity; Feedback regulation; Document; Information; Interest; Relevance; Cause; Topic; Blog; Use; Information retrieval; Document retrieval; Deterioration; Influence; Paper; Local scope; Problem; Performance; Web site
• ISSN: 1386-4564; 1573-7659; 1573-7659
• DOI: 10.1007/s10791-011-9176-6

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.