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Exploiting Synergy Between Ontologies and Recommender Systems

Exploiting Synergy Between Ontologies and Recommender Systems
Exploiting Synergy Between Ontologies and Recommender Systems
Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured.
Middleton, Stuart E.
404b62ba-d77e-476b-9775-32645b04473f
Alani, Harith
70cdbdce-1494-44c2-9dae-65d82bf7e991
Shadbolt, Nigel R.
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Roure, David C. De
02879140-3508-4db9-a7f4-d114421375da
Middleton, Stuart E.
404b62ba-d77e-476b-9775-32645b04473f
Alani, Harith
70cdbdce-1494-44c2-9dae-65d82bf7e991
Shadbolt, Nigel R.
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Roure, David C. De
02879140-3508-4db9-a7f4-d114421375da

Middleton, Stuart E., Alani, Harith, Shadbolt, Nigel R. and Roure, David C. De (2002) Exploiting Synergy Between Ontologies and Recommender Systems. Semantic Web Workshop 2002 At the Eleventh International World Wide Web Conference Hawaii, USA.

Record type: Conference or Workshop Item (Paper)

Abstract

Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender systems do, however, suffer from cold-start problems where no initial information is available early on upon which to base recommendations. Semantic knowledge structures, such as ontologies, can provide valuable domain knowledge and user information. However, acquiring such knowledge and keeping it up to date is not a trivial task and user interests are particularly difficult to acquire and maintain. This paper investigates the synergy between a web-based research paper recommender system and an ontology containing information automatically extracted from departmental databases available on the web. The ontology is used to address the recommender systems cold-start problem. The recommender system addresses the ontology's interest-acquisition problem. An empirical evaluation of this approach is conducted and the performance of the integrated systems measured.

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More information

Published date: May 2002
Additional Information: Semantic Web Workshop 2002 At the Eleventh International World Wide Web Conference Hawaii, USA Organisation: ACM Address: Hawaii, USA
Venue - Dates: Semantic Web Workshop 2002 At the Eleventh International World Wide Web Conference Hawaii, USA, 2002-05-01
Organisations: Web & Internet Science, Electronics & Computer Science, IT Innovation

Identifiers

Local EPrints ID: 256487
URI: https://eprints.soton.ac.uk/id/eprint/256487
PURE UUID: a26cea30-4244-4d2f-9b51-5842e91efdec
ORCID for Stuart E. Middleton: ORCID iD orcid.org/0000-0001-8305-8176
ORCID for David C. De Roure: ORCID iD orcid.org/0000-0001-9074-3016

Catalogue record

Date deposited: 15 Apr 2002
Last modified: 06 Jun 2018 13:20

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Contributors

Author: Stuart E. Middleton ORCID iD
Author: Harith Alani
Author: Nigel R. Shadbolt
Author: David C. De Roure ORCID iD

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