Databases Theory and Applications


Databases Theory and Applications


Editors: Mohamed A. Sharaf, Muhammad Aamir Cheema, Jianzhong Qi

Contributing authors: Haishuai Wang, Peng Zhang, Ling Chen, Chengqi Zhang


Document Type

Conference Proceeding


Haishuai Wang (with Peng Zhang, Ling Chen, Chengqi Zhang) is a contributing author, " SocialAnalysis: A Real-time Query and Mining System from Social Media Data Streams."

Book Introduction:

This book constitutes the refereed proceedings of the 26th Australasian Database Conference, ADC 2015, held in Melbourne, VIC, Australia, in June 2015. The 24 full papers presented together with 5 demo papers were carefully reviewed and selected from 43 submissions. The Australasian Database Conference is an annual international forum for sharing the latest research advancements and novel applications of database systems, data driven applications and data analytics between researchers and practitioners from around the globe, particularly Australia and New Zealand. The mission of ADC is to share novel research solutions to problems of today’s information society that fulfill the needs of heterogeneous applications and environments and to identify new issues and directions for future research. ADC seeks papers from academia and industry presenting research on all practical and theoretical aspects of advanced database theory and applications, as well as case studies and implementation experiences.

Paper abstract:

In this paper, we present our recent progress of designing a real-time system, SocialAnalysis, to discover and summarize emergent social events from social media data streams. In social networks era, people always frequently post messages or comments about their activities and opinions. Hence, there exist temporal correlations between the physical world and virtual social networks, which can help us to monitor and track social events, detecting and positioning anomalous events before their outbreakings, so as to provide early warning. The key technologies in the system include: (1) Data denoising methods based on multi-features, which screens out the query-related event data from massive background data. (2) Abnormal events detection methods based on statistical learning, which can detect anomalies by analyzing and mining a series of observations and statistics on the time axis. (3) Geographical position recognition, which is used to recognize regions where abnormal events may happen.



Publication Date


Publication Information

Wang H., Zhang P., Chen L., Zhang C. (2015) SocialAnalysis: A Real-Time Query and Mining System from Social Media Data Streams. In: Sharaf M., Cheema M., Qi J. (eds) Databases Theory and Applications. ADC 2015. Lecture Notes in Computer Science, vol 9093. Springer, Cham.


© Springer International Publishing Switzerland 2015

Databases Theory and Applications