LINEAR STRUCTURE IN INFORMATION RETRIEVAL

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We also discuss a practical procedure to determine the linear ... In this paper, we focus more on the performance issues of a linear system and use an ..... An exact or approximate solution of this system of linear inequalities can be found by.
LINEAR

STRUCTURE

S.K.M.

IN INFORMATION

Wong,

Y.Y. Yao and

RETRIEVAL

P. Bollmann

Abstract Based on the concept information retrieval.

linear decision mental

of user preference, we investigate the linear structure in We also discuss a practical procedure to determine the

function

and present an analysis of term weighting. Our experiprovides a useful framework

seem to demonstrate that our model for the design of an adaptive system.

1.

results

Introduction

Bollmann and Wong[BOLL87] have proposed an adaptive linear retrieval One of the main objectives of their work is to establish a theoreticat basis for Although they investigated the necessary adopting linear models in information retrieval. and sufficient conditions for the existence of a linear retrieval function based on measurement theory, some of the important issues have not been fully explored. Recently,

model.

In this paper, we focus more on the performance iterative

function. present

(a gradient

algorithm

In particular, an analysis

results[SALT;Il,

descent

as an example

of term weighting

SALT83,

RIJS79]

procedure)

issues of a linear system and use an

to compute

the coefficients

for illustrating

the usefulness

for auto-indexing

and show

of a linear

of our approach,

we

that some of the earlier

can perhaps be better understood

based on the linear

structure. Our experimental results seem to demonstrate that our linear model useful framework for designing an adaptive system for information retrieval.

provides

a

S.K.M. Wong and Y.Y. Yao, Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada S4S OA2. P. Bollmann, Technische Universitat, Berlin, Germany.

Permission to copy without fee all part of this material is granted provided that the copies arc not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear. and notice is given that copying is by permission of the Association for Cotnputing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. C

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O-89791-274-8

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The paper is organized as follows. In Section 2. we first review the concept of user preference which forms the basis of our discussion.. Then we concentrate on the study of a linear system in Section 3. En Section 4, we show how to construct a linear decision function by adopting an acceptab’le ranking strategy and compare our results with those obtained by other methods. The experimental results are summarized in Section 5. The main objectives of our experiments are to demonstrate the linear structure of some test document collections and to evaluate the performance of our method.

2. IJscr Preference Given any two documents in a collection, we assume that a user would ~@ZV- one to the other or regard both of them as being equivalent with respect to his information needs. In other words, it is assumed that the user’s judgment on a set of documents D can be described by a (strict) preference relation c* , namely, d

the user prefers

d’ to d ,

This reIation implies that there also exists an indifference c=>

d-d’

A preference properties: (i) (ii)

If d