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EventCube: Multi-Dimensional Search and Mining of Structured and Text Data

Fangbao Tao, et al., and Bolin Ding

Abstract

A large portion of real world data is either text or structured (e.g., relational) data. Moreover, such data objects are often linked together (e.g., structured specification of products linking with the corresponding product descriptions and customer comments). Even for text data such as news data, typed entities can be extracted with entity extraction tools. The EventCube project constructs TextCube and TopicCube from interconnected structured and text data (or from text data via entity extraction and dimension building), and performs multidimensional search and analysis on such datasets, in an informative, powerful, and userfriendly manner. This proposed EventCube demo will show the power of the system not only on the originally designed ASRS (Aviation Safety Report System) data sets, but also on news datasets collected from multiple news agencies, and academic datasets constructed from the DBLP and web data. The system has high potential to be extended in many powerful ways and serve as a general platform for search, OLAP (online analytical processing) and data mining on integrated text and structured data. After the system demo in the conference, the system will be put on the web for public access and evaluation.

Details

Publication typeProceedings
Published inProceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2013)
PublisherACM – Association for Computing Machinery
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