Extract-biased pseudo-revelance feedback
نویسندگان
چکیده
منابع مشابه
Extract-biased pseudo-revelance feedback
Successfully retrieving a web document is a twofold problem: having an adequate query that can usefully and properly help filtering relevant documents from huge collections, and presenting the user those that will indeed fulfill his/her needs. In this paper, we focus on the first issue – the problem of having a misleading user query. The aim of the work is to refine a query by using extracts in...
متن کاملExtract-biased pseudo-relevance feedback
Successfully retrieving a web document is a twofold problem: having an adequate query that can usefully and properly help filtering relevant documents from huge collections, and presenting the user those that may indeed fulfill his/her needs. In this paper, we focus on the first issue – the problem of having a misleading user query. The aim of the work is to refine a query by using extracts ins...
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Query-biased pseudo relevance feedback creates document representations for document feedback that aim to be more relevant to the user than using the entire document. Our submitted runs using querybiased feedback degraded performance compared to not using feedback. The cause of this degradation was the use of too many documents for feedback. Preliminary document retrieval experiments using fewe...
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We propose a structure cognizant framework for pseudo relevance feedback (PRF). This has an application, for example, in selecting expansion terms for general search from subsets such as Wikipedia, wherein documents typically have a minimally fixed set of fields, viz., Title, Body, Infobox and Categories. In existing approaches to PRF based expansion, weights of expansion terms do not depend on...
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ژورنال
عنوان ژورنال: INTELIGENCIA ARTIFICIAL
سال: 2007
ISSN: 1988-3064,1137-3601
DOI: 10.4114/ia.v11i36.890