Location-aware group preference queries in social-networks

Ammar Sohail, Arif Hidayat, Muhammad Aamir Cheema, David Taniar

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

    Abstract

    With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.

    Original languageEnglish
    Title of host publicationDatabases Theory and Applications
    Subtitle of host publication29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings
    EditorsJunhu Wang, Gao Cong, Jinjun Chen, Jianzhong Qi
    Place of PublicationCham Switzerland
    PublisherSpringer
    Pages53-67
    Number of pages15
    ISBN (Electronic)9783319920139
    ISBN (Print)9783319920122
    DOIs
    Publication statusPublished - 1 Jan 2018
    EventAustralasian Database Conference 2018 - Griffith University, Gold Coast, Australia
    Duration: 23 May 201825 May 2018
    Conference number: 23rd
    http://www.ict.griffith.edu.au/conferences/adc2018/

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Volume10837
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceAustralasian Database Conference 2018
    Abbreviated titleADC 2018
    CountryAustralia
    CityGold Coast
    Period23/05/1825/05/18
    Internet address

    Cite this

    Sohail, A., Hidayat, A., Cheema, M. A., & Taniar, D. (2018). Location-aware group preference queries in social-networks. In J. Wang, G. Cong, J. Chen, & J. Qi (Eds.), Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings (pp. 53-67). (Lecture Notes in Computer Science; Vol. 10837). Cham Switzerland: Springer. https://doi.org/10.1007/978-3-319-92013-9_5
    Sohail, Ammar ; Hidayat, Arif ; Cheema, Muhammad Aamir ; Taniar, David. / Location-aware group preference queries in social-networks. Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings. editor / Junhu Wang ; Gao Cong ; Jinjun Chen ; Jianzhong Qi. Cham Switzerland : Springer, 2018. pp. 53-67 (Lecture Notes in Computer Science).
    @inproceedings{769868dff6b2468582d17d86d6f46b22,
    title = "Location-aware group preference queries in social-networks",
    abstract = "With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.",
    author = "Ammar Sohail and Arif Hidayat and Cheema, {Muhammad Aamir} and David Taniar",
    year = "2018",
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    Sohail, A, Hidayat, A, Cheema, MA & Taniar, D 2018, Location-aware group preference queries in social-networks. in J Wang, G Cong, J Chen & J Qi (eds), Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings. Lecture Notes in Computer Science, vol. 10837, Springer, Cham Switzerland, pp. 53-67, Australasian Database Conference 2018, Gold Coast, Australia, 23/05/18. https://doi.org/10.1007/978-3-319-92013-9_5

    Location-aware group preference queries in social-networks. / Sohail, Ammar; Hidayat, Arif; Cheema, Muhammad Aamir; Taniar, David.

    Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings. ed. / Junhu Wang; Gao Cong; Jinjun Chen; Jianzhong Qi. Cham Switzerland : Springer, 2018. p. 53-67 (Lecture Notes in Computer Science; Vol. 10837).

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

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    T1 - Location-aware group preference queries in social-networks

    AU - Sohail, Ammar

    AU - Hidayat, Arif

    AU - Cheema, Muhammad Aamir

    AU - Taniar, David

    PY - 2018/1/1

    Y1 - 2018/1/1

    N2 - With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.

    AB - With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.

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    Sohail A, Hidayat A, Cheema MA, Taniar D. Location-aware group preference queries in social-networks. In Wang J, Cong G, Chen J, Qi J, editors, Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings. Cham Switzerland: Springer. 2018. p. 53-67. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-92013-9_5