TY - GEN
T1 - In Good Company: Efficient Retrieval of the Top-k Most Relevant Event-Partner Pairs
AU - Wu, Dingming
AU - Zhu, Yi
AU - Jensen, Christian S.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - https://link.springer.com/chapter/10.1007%2F978-3-030-18579-4_31
U2 - 10.1007/978-3-030-18579-4_31
DO - 10.1007/978-3-030-18579-4_31
M3 - Article in proceeding
SN - 9783030185787
T3 - Lecture Notes in Computer Science (LNCS)
SP - 519
EP - 535
BT - Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Proceedings
A2 - Natwichai, Juggapong
A2 - Li, Guoliang
A2 - Yang, Jun
A2 - Gama, Joao
A2 - Tong, Yongxin
PB - Springer
T2 - International Conference on Database Systems for Advanced Applications
Y2 - 22 April 2019 through 25 April 2019
ER -