A Personalised Recommendation System for Context-Aware Suggestions

Andrei Rikitianskii, Morgan Harvey, Fabio Crestani

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

12 Citations (Scopus)

Abstract

The recently introduced TREC Contextual Suggestion track proposes the problem of suggesting contextually relevant places to a user visiting a new city based on his/her preferences and the location of the new city. In this paper we introduce a more sophisticated approach to this problem which very carefully constructs user profiles in order to provide more accurate and relevant recommendations. Based on the track evaluations we demonstrate that our system not only significantly outperforms a baseline method but also performs very well in comparison to other runs submitted to the track, managing to achieve the best results in nearly half of all test contexts.
Original languageEnglish
Title of host publicationAdvances in Information Retrieval
EditorsMaarten de Rijke, Tom Kenter, Arjen P. de Vries, ChengXiang Zhai, Franciska de Jong, Kira Radinsky, Katja Hofmann
Place of PublicationLondon
PublisherSpringer
Pages63-74
Volume8416
ISBN (Print)978-3-319-06027-9
DOIs
Publication statusPublished - 2014
EventAdvances in Information Retrieval - 36th European Conference on {IR} Research, {ECIR} 2014, Amsterdam, The Netherlands, April 13-16, 2014. Proceedings -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

Conference

ConferenceAdvances in Information Retrieval - 36th European Conference on {IR} Research, {ECIR} 2014, Amsterdam, The Netherlands, April 13-16, 2014. Proceedings
Period1/01/14 → …

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