Open AccessSLOQUE
Author(s) -
Maggy Anastasia Suryanto,
EePeng Lim,
Aixin Sun,
Roger H.L. Chiang
Publication year - 2007
Publication title -
institutional knowledge (ink) - institutional knowledge at singapore management university (singapore management university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/1317353.1317364
Subject(s) - computer science , query expansion , information retrieval , term (time) , task (project management) , web query classification , scheme (mathematics) , query optimization , web search query , sargable , ranking (information retrieval) , query language , search engine , mathematics , mathematical analysis , physics , quantum mechanics , management , economics
Searching answers to complex questions is a challenging IR task. In this paper, we examine the use of query templates with semantic slots to formulate slot-based queries. These queries have query terms assigned to entity and relationship slots. We develop several query expansion methods for slot-based queries so as to improve their retrieval effectiveness on a document collection. Each method consists of a combination of term scoring scheme, term scoring formula, and term assignment scheme. Our preliminary experiments evaluate these different slot-based query expansion methods on a collection of news documents,and conclude that:(1) slot-based queries yield better retrieval accuracy compared to keyword-based queries in the complex question problems; and (2)directly applying traditional query expansion on the query terms of each slot does not always work well
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