Ontology-based personalised retrieval in support of reminiscence

Shi, Lei and Setchi, Rossitza ORCID: https://orcid.org/0000-0002-7207-6544 2013. Ontology-based personalised retrieval in support of reminiscence. Knowledge-Based Systems 45 , pp. 47-61. 10.1016/j.knosys.2013.02.004

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Abstract

This research proposes a knowledge-based framework for integrating ontology-based personalised retrieval and reminiscence support. The aim is to assist people in recalling, browsing and re-discovering events from their lives by considering their profiles and background knowledge and providing them with customised information retrieval. To model a user’s background knowledge, this paper defines a user profile space (UPS) model and describes its construction method. The model has a dynamic structure based on relevance feedback and interactions with users. Furthermore, this work introduces a multi-ontology query expansion model which uses user-oriented ontologies, UPSs and semantic feature-selection algorithms to expand queries. In this model, knowledge-spanning trees are generated from ontology/UPS graphs based on the queries. These knowledge-spanning trees contain semantic features which enhance the representations of the original queries and further facilitate personalised retrieval on a semantic basis. The experimental results indicate that the proposed approach consistently outperforms term-based retrieval on precision, recall and f-score, which proves the positive effect of using ontology/user profile spaces in query expansion and personalised retrieval.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Uncontrolled Keywords:	Ontology graph; User profile space; Knowledge spanning tree; Feature selection; Personalised retrieval; Reminiscence support
Publisher:	Elsevier
ISSN:	0950-7051
Last Modified:	06 Jul 2023 10:18
URI:	https://orca.cardiff.ac.uk/id/eprint/45523

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