Theory-based user modeling for personalized interactive information retrieval

2.50
Hdl Handle:
http://hdl.handle.net/10547/622040
Title:
Theory-based user modeling for personalized interactive information retrieval
Authors:
Ullah, Asad; Liu, Haiming
Abstract:
In an effort to improve users’ search experiences during their information seeking process, providing a personalized information retrieval system is proposed to be one of the effective approaches. To personalize the search systems requires a good understanding of the users. User modeling has been approved to be a good method for learning and representing users. Therefore many user modeling studies have been carried out and some user models have been developed. The majority of the user modeling studies applies inductive approach, and only small number of studies employs deductive approach. In this paper, an EISE (Extended Information goal, Search strategy and Evaluation threshold) user model is proposed, which uses the deductive approach based on psychology theories and an existing user model. Ten users’ interactive search log obtained from the real search engine is applied to validate the proposed user model. The preliminary validation results show that the EISE model can be applied to identify different types of users. The search preferences of the different user types can be applied to inform interactive search system design and development.
Affiliation:
University of Bedfordshire
Citation:
Ullah A, Liu H (2016) 'Theory-based user modeling for personalized interactive information retrieval', Conference on User Modeling Adaptation and Personalization - Halifax, NS, Canada, ACM.
Issue Date:
17-Jul-2016
URI:
http://hdl.handle.net/10547/622040
Additional Links:
http://ceur-ws.org/Vol-1618/HAAPIE_paper3.pdf
Type:
Conference papers, meetings and proceedings
Language:
en
Appears in Collections:
Computing

Full metadata record

DC FieldValue Language
dc.contributor.authorUllah, Asaden
dc.contributor.authorLiu, Haimingen
dc.date.accessioned2017-03-02T13:40:33Z-
dc.date.available2017-03-02T13:40:33Z-
dc.date.issued2016-07-17-
dc.identifier.citationUllah A, Liu H (2016) 'Theory-based user modeling for personalized interactive information retrieval', Conference on User Modeling Adaptation and Personalization - Halifax, NS, Canada, ACM.en
dc.identifier.urihttp://hdl.handle.net/10547/622040-
dc.description.abstractIn an effort to improve users’ search experiences during their information seeking process, providing a personalized information retrieval system is proposed to be one of the effective approaches. To personalize the search systems requires a good understanding of the users. User modeling has been approved to be a good method for learning and representing users. Therefore many user modeling studies have been carried out and some user models have been developed. The majority of the user modeling studies applies inductive approach, and only small number of studies employs deductive approach. In this paper, an EISE (Extended Information goal, Search strategy and Evaluation threshold) user model is proposed, which uses the deductive approach based on psychology theories and an existing user model. Ten users’ interactive search log obtained from the real search engine is applied to validate the proposed user model. The preliminary validation results show that the EISE model can be applied to identify different types of users. The search preferences of the different user types can be applied to inform interactive search system design and development.en
dc.language.isoenen
dc.relation.urlhttp://ceur-ws.org/Vol-1618/HAAPIE_paper3.pdfen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjecthuman-centred computingen
dc.subjectinformation retrievalen
dc.subjectuser modellingen
dc.subjectpersonalisationen
dc.subjectG440 Human-computer Interactionen
dc.titleTheory-based user modeling for personalized interactive information retrievalen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentUniversity of Bedfordshireen
dc.date.updated2017-03-02T13:30:16Z-
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