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Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/62487

Title: A Framework for the Evaluation of Adaptive IR Systems through Implicit Recommendation
Other Titles: International Workshop on Task Specific Information Retrieval, TSIR 2011, at the 19th International Conference on Conceptual Structures for Discovering Knowledge
Author: SHARP, MARY
LAWLESS, SEAMUS
MULWA, CATHERINE
WADE, VINCENT PATRICK
GHORAB, MOHAMMED RAMI ELHUSSEIN
O'DONNELL, EILEEN
Sponsor: 
Name Grant Number
07/CE/I1142

Author's Homepage: http://people.tcd.ie/selawles
http://people.tcd.ie/msharp
http://people.tcd.ie/vwade
http://people.tcd.ie/ghorabm
http://people.tcd.ie/odonnee
Keywords: Computer Science and Engineering
Personalised Information Retrieval Systems
Issue Date: 2011
Publisher: Springer-Verlag LNCS
Citation: Catherine Mulwa, Séamus Lawless, M. Rami Ghorab, Eileen O'Donnell, Mary Sharp and Vincent Wade, A Framework for the Evaluation of Adaptive IR Systems through Implicit Recommendation, International Workshop on Task Specific Information Retrieval, TSIR 2011, at the 19th International Conference on Conceptual Structures for Discovering Knowledge, University of Derby, England, 25th-29th July, Simon Andrews, Simon Polovina, Richard Hill and Babak Akhgar, 6828, 6828, Springer-Verlag LNCS, 2011, 366 - 374
Series/Report no.: 6828;
6828;
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.
Description: PUBLISHED
URI: http://hdl.handle.net/2262/62487
Related links: http://www.springerlink.com/content/d02l908883t5344k/fulltext.pdf
http://www.scss.tcd.ie/seamus.lawless/papers/TSIR2011.pdf
Appears in Collections:Computer Science (Scholarly Publications)

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