Content-aware hierarchical point-of-interest embedding model for successive POI recommendation

Buru Chang, Yonggyu Park, Donghyeon Park, Seongsoon Kim, Jaewoo Kang

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

    81 Citations (Scopus)

    Abstract

    Recommending a point-of-interest (POI) a user will visit next based on temporal and spatial context information is an important task in mobile-based applications. Recently, several POI recommendation models based on conventional sequential-data modeling approaches have been proposed. However, such models focus on only a user's check-in sequence information and the physical distance between POIs. Furthermore, they do not utilize the characteristics of POIs or the relationships between POIs. To address this problem, we propose CAPE, the first content-aware POI embedding model which utilizes text content that provides information about the characteristics of a POI. CAPE consists of a check-in context layer and a text content layer. The check-in context layer captures the geographical influence of POIs from the check-in sequence of a user, while the text content layer captures the characteristics of POIs from the text content. To validate the efficacy of CAPE, we constructed a large-scale POI dataset. In the experimental evaluation, we show that the performance of the existing POI recommendation models can be significantly improved by simply applying CAPE to the models.

    Original languageEnglish
    Title of host publicationProceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
    EditorsJerome Lang
    PublisherInternational Joint Conferences on Artificial Intelligence
    Pages3301-3307
    Number of pages7
    ISBN (Electronic)9780999241127
    DOIs
    Publication statusPublished - 2018
    Event27th International Joint Conference on Artificial Intelligence, IJCAI 2018 - Stockholm, Sweden
    Duration: 2018 Jul 132018 Jul 19

    Publication series

    NameIJCAI International Joint Conference on Artificial Intelligence
    Volume2018-July
    ISSN (Print)1045-0823

    Other

    Other27th International Joint Conference on Artificial Intelligence, IJCAI 2018
    Country/TerritorySweden
    CityStockholm
    Period18/7/1318/7/19

    ASJC Scopus subject areas

    • Artificial Intelligence

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