Title of article
Local search: A guide for the information retrieval practitioner
Author/Authors
Andrew MacFarlane، نويسنده , , Andrew Tuson، نويسنده ,
Issue Information
دوماهنامه با شماره پیاپی سال 2009
Pages
16
From page
159
To page
174
Abstract
There are a number of combinatorial optimisation problems in information retrieval in which the use of local search methods are worthwhile. The purpose of this paper is to show how local search can be used to solve some well known tasks in information retrieval (IR), how previous research in the field is piecemeal, bereft of a structure and methodologically flawed, and to suggest more rigorous ways of applying local search methods to solve IR problems. We provide a query based taxonomy for analysing the use of local search in IR tasks and an overview of issues such as fitness functions, statistical significance and test collections when conducting experiments on combinatorial optimisation problems. The paper gives a guide on the pitfalls and problems for IR practitioners who wish to use local search to solve their research issues, and gives practical advice on the use of such methods. The query based taxonomy is a novel structure which can be used by the IR practitioner in order to examine the use of local search in IR.
Keywords
combinatorial optimisation , information retrieval , evaluation , Local search
Journal title
Information Processing and Management
Serial Year
2009
Journal title
Information Processing and Management
Record number
1228910
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