Relevance Models for Multi-Contextual Appropriateness in Point-of-Interest Recommendation

Anirban Chakraborty, Debasis Ganguly, Owen Conlan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Trip-qualifiers, such as 'trip-type' (vacation, work etc.), 'accompanied-by' (e.g., solo, friends, family etc.) are potentially useful sources of information that could be used to improve the effectiveness of POI recommendation in a current context (with a given set of these constraints). Using such information is not straight forward because a user's text reviews about the POIs visited in the past do not explicitly contain such annotations (e.g., a positive review about a pub visit does not contain the information on whether the user was with friends or alone, on a business trip or vacation). We propose to use a small set of manually compiled knowledge resource to predict the associations between the review texts in a user profile and the likely trip contexts. We demonstrate that incorporating this information within an IR-based relevance modeling framework significantly improves POI recommendation.
Original languageEnglish
Title of host publicationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery, Inc
Pages1981–1984
ISBN (Print)9781450380164
DOIs
Publication statusPublished - 25 Jul 2020
Event43rd International ACM SIGIR Conference on Research and Development in Information Retrieval - Online Conference
Duration: 25 Jul 202030 Jul 2020
Conference number: 43
https://sigir.org/sigir2020/

Publication series

NameSIGIR '20
PublisherAssociation for Computing Machinery

Conference

Conference43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Abbreviated titleSIGIR 2020
Period25/07/2030/07/20
Internet address

Keywords

  • joint context modeling
  • weak supervision
  • point-of-interest recommendation

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