Type

Conference Proceedings

Authors

Eileen O'Donnell
Mary Sharp
Vincent Wade
Catherine Mulwa
Seamus Lawless
Mohammed Rami Elhussein Ghorab

Subjects

Computer Science

Topics
personalised information retrieval systems smart sustainable planet web based intelligent content communications evaluation metrics computer science and engineering recommendation systems access information

A Framework for the Evaluation of Adaptive IR Systems through Implicit Recommendation (2011)

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.
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Full list of authors on original publication

Eileen O'Donnell, Mary Sharp, Vincent Wade, Catherine Mulwa, Seamus Lawless, Mohammed Rami Elhussein Ghorab

Experts in our system

1
Eileen O'Donnell
TU Dublin
Total Publications: 28
 
2
Vincent Patrick Wade
Trinity College Dublin
Total Publications: 140
 
3
Seamus Lawless
Trinity College Dublin
Total Publications: 71
 
4
Mohammed Rami Elhussein Ghorab
Trinity College Dublin
Total Publications: 14