Alkhawaldeh, R. S., Padmanabhan, D., Jose, J. M. and Yuan, F. (2017) LTRo: Learning to Route Queries in Clustered P2P IR. In: ECIR 2017, Aberdeen, Scotland, 9-13 April 2017, pp. 513-519. (doi: 10.1007/978-3-319-56608-5_42)
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141444.pdf - Accepted Version 572kB |
Abstract
Query Routing is a critical step in P2P Information Retrieval. In this paper, we consider learning to rank approaches for query routing in the clustered P2P IR architecture. Our formulation, LTRo, scores resources based on the number of relevant documents for each training query, and uses that information to build a model that would then rank promising peers for a new query. Our empirical analysis over a variety of P2P IR testbeds illustrate the superiority of our method against the state-of-the-art methods for query routing.
| Item Type: | Conference Proceedings |
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| Additional Information: | Published in Lecture Notes in Computer Science, v. 10193, pp. 513-519. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Jose, Professor Joemon and Alkhawaldeh, Mr Rami Suleiman |
| Authors: | Alkhawaldeh, R. S., Padmanabhan, D., Jose, J. M., and Yuan, F. |
| College/School: | College of Science and Engineering > School of Computing Science |
| ISSN: | 0302-9743 |
| Published Online: | 08 April 2017 |
| Copyright Holders: | Copyright © 2017 Springer International Publishing AG 2 |
| First Published: | First published in Lecture Notes in Computer Science 10193: 513-519 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
| Related URLs: |
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