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In Good Company: Efficient Retrieval of the Top-k Most Relevant Event-Partner Pairs

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Database Systems for Advanced Applications (DASFAA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11447))

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Abstract

The proliferation of event-based social networking (ESBN) motivates a range of studies on topics such as event, venue, and friend recommendation and event creation and organization. In this setting, the notion of event-partner recommendation has recently attracted attention. When recommending an event to a user, this functionality allows recommendation of partner with whom to attend the event. However, existing proposals are push-based: recommendations are pushed to users at the system’s initiative. In contrast, EBSNs provide users with keyword-based search functionality. This way, users may retrieve information in pull mode. We propose a new way of accessing information in EBSNs that combines push and pull, thus allowing users to not only conduct ad-hoc searches for events, but also to receive partner recommendations for retrieved events. Specifically, we define and study the top-k event-partner (kEP) pair retrieval query that integrates event-partner recommendation and keyword-based search for events. The query retrieves event-partner pairs, taking into account the relevance of events to user-supplied keywords and so-called together preferences that indicate the extent of a user’s preference to attend an event with a given partner. In order to compute kEP queries efficiently, we propose a rank-join based framework with three optimizations. Results of empirical studies with implementations of the proposed techniques demonstrate that the proposed techniques are capable of excellent performance.

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Notes

  1. 1.

    http://www.meetup.com.

  2. 2.

    http://www.eventbrite.com.

  3. 3.

    http://www.meetup.com.

  4. 4.

    https://lucene.apache.org.

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Authors and Affiliations

  1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

    Dingming Wu & Yi Zhu

  2. Department of Computer Science, Aalborg University, Aalborg, Denmark

    Christian S. Jensen

Authors
  1. Dingming Wu
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  2. Yi Zhu
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  3. Christian S. Jensen
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Corresponding author

Correspondence to Dingming Wu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Guoliang Li

  2. Duke University, Durham, NC, USA

    Jun Yang

  3. University of Porto, Porto, Portugal

    Joao Gama

  4. Chiang Mai University, Chiang Mai, Thailand

    Juggapong Natwichai

  5. Beihang University, Beijing, China

    Yongxin Tong

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Wu, D., Zhu, Y., Jensen, C.S. (2019). In Good Company: Efficient Retrieval of the Top-k Most Relevant Event-Partner Pairs. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11447. Springer, Cham. https://doi.org/10.1007/978-3-030-18579-4_31

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  • DOI: https://doi.org/10.1007/978-3-030-18579-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18578-7

  • Online ISBN: 978-3-030-18579-4

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