Exploiting Ontological Structure for Complex Preference Assembly

Authors:
Gil Chamiel;Maurice Pagnucco
Affiliations:
School of Computer Science and Engineering, The University of New South Wales, NSW, Sydney 2052, Australia and NICTA, Sydney, Australia;School of Computer Science and Engineering, The University of New South Wales, NSW, Sydney 2052, Australia and NICTA, Sydney, Australia
Venue:
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

Citing 6
Cited 0

Ontological user profiling in recommender systems

ACM Transactions on Information Systems (TOIS)
Verbs semantics and lexical selection

ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Through different eyes: assessing multiple conceptual views for querying web services

Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Inferring user's preferences using ontologies

AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
The fundamentals of iSPARQL: a virtual triple approach for similarity-based semantic web tasks

ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Querying the semantic web with preferences

ISWC'06 Proceedings of the 5th international conference on The Semantic Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

When a user is looking for a product recommendation they usually lack expert knowledge regarding the items they are looking for. Ontologies on the other hand are crafted by experts and therefore provide a rich source of information for enhancing preferences. In this paper we significantly extend previous work on exploiting ontological information by allowing the user to specify preferences in a more expressive manner. Rather than allowing for only one preferred target concept, we allow a `chain' of user preferences. Furthermore, we treat information from the underlying ontology of the domain as a secondary preference structure. We then show how to assemble these two preference structures (user and ontology) into a preference over items.