Paper Info
Title
A framework for the evaluation of adaptive IR systems through implicit recommendation
Abstract
Personalised Information Retrieval (PIR) has gained considerable attention in recent literature. In PIR different stages of the retrieval process are adapted to the user, such as adapting the user's query or the results. Personalised recommender frameworks are endowed with intelligent mechanisms to search for products, goods and services that users are interested in. The objective of such tools is to evaluate and filter the huge amount of information available within a specific scope to assist users in their information access processes. This paper presents a web-based adaptive framework for evaluating personalised information retrieval systems. The framework uses implicit recommendation to guide users in deciding which evaluation techniques, metrics and criteria to use. A task-based experiment was conducted to test the functionality and performance of the framework. A Review of evaluation techniques for personalised IR systems was conducted and the results of the analysed survey are presented.
Year
Venue
Keywords
2011
ICCS
web-based adaptive framework,information access process,analysed survey,personalised information retrieval system,evaluation technique,implicit recommendation,pir different stage,retrieval process,personalised ir system,personalised information retrieval,personalised recommender framework,adaptive ir system,personalisation
Field
DocType
Volume
World Wide Web,Computer science,Goods and services,Information access,Computer Science and Engineering,Personalization
Conference
6828.0
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
15
6
Name
Order
Citations
PageRank
Catherine Mulwa1312.29
Seamus Lawless215513.27
M. Rami Ghorab3698.08
Eileen O'Donnell400.34
Mary Sharp5312.63
Vincent Wade6252.23