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資訊系統與應用研究所
[Dec-19] Efficient Processing of Group Queries for Social Applications

Seminar of Institute of Information Systems and Applications

Speaker :

 Prof. Yi-Ling Chen陳怡伶教授

Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology

Topic :

Efficient Processing of Group Queries for Social Applications

Date :

13:30-15:00 Wednesday 19-Dec-2018

Place :

台達館R105Delta Building R105

Host :

Prof. Chih Ya Shen

 

Bio

Yi-Ling Chen received the BS degree from the Department of Computer Science and Information Engineering, National Chiao Tung University, Hsinchu, Taiwan. She received her PhD degree from the Department of Electrical Engineering, National Taiwan University, Taipei. She is now an assistant professor of the Department of Computer Science and Information Engineering in National Taiwan University of Science and Technology. Her research interests include social network analysis, data mining, and pervasive computing.

 

Abstract:

Three essential criteria are important for social activity planning: (1) finding attendees familiar with the initiator, (2) ensuring most attendees have tight social relations with each other, and (3) selecting an activity period available to all. Therefore, we propose the Social-Temporal Group Query (STGQ) to find suitable time and attendees with minimum total social distance. We first prove that the problem is NP-hard and inapproximable within any ratio. Next, we design two algorithms, SGSelect and STGSelect, which include effective pruning techniques to substantially reduce running time. Moreover, as users may iteratively adjust query parameters to fine tune the results, we further study the problem of Subsequent Social Group Query (SSGQ). We propose the Accumulative Search Tree and Social Boundary, to cache and index intermediate results of previous queries in order to accelerate subsequent query processing. Experimental results indicate that SGSelect and STGSelect are significantly more efficient than baseline approaches. With the caching mechanisms, processing time of subsequent queries can be further reduced by 50%-75%. We conduct a user study to compare the proposed approach with manual activity coordination. The results show that our approach obtains higher quality solutions with lower coordination effort, thereby increasing users’ willingness to organize activities.

 

All faculties and students are welcome to join.

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