Towards Geosocial Recommender Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)

Abstract

The usage of social networks sites (SNSs), such as Facebook, and geosocial networks (GSNs), such as Foursquare, has increased tremendously over the past years. The willingness of users to share their current locations and experiences facilitate the creation of geographical recommender systems based on user generated content (UGC). This idea has been used to create a substantial amount of geosocial recommender systems (GRSs), such as Gogobot, TripIt, and Trippy already, but can be applied to more complex scenarios, such as the recommendation of products with a strong binding to their region, such as real estate or vacation destinations. This extended form of GRS development requires advanced functionality for information collection (from the web, other social media and sensors), information enrichment (such as data quality assessment and advanced data analysis), and personalized recommendations. The creation of a toolset to cope with these challenges is the goal of this research project, for which the outline is presented in this paper.
Original languageEnglish
Title of host publication4th International Workshop on Web Intelligence & Communities (WI&C 2012)
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages8:1-8:4
Number of pages4
ISBN (Print)978-1-4503-1189-2
DOIs
Publication statusPublished - 16 Apr 2012
Event4th International Workshop on Web Intelligence & Communities, WI&C 2012 - Lyon, France
Duration: 16 Apr 201216 Apr 2012

Workshop

Workshop4th International Workshop on Web Intelligence & Communities, WI&C 2012
Period16/04/1216/04/12
Other16 April 2012

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