This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). This proposal seeks to address a wide range of research challenges involving OLAP (OnLine Analytical Processing). This collaborative project is concerned with increasing the ability for analytical processing for information networks. Information networks have been expanding rapidly and attract broad scholarly interest ranging from intrusion pattern detection to social community discovery. Typical information networks include communication networks, social networks, the Web, and biological networks. In contrast to the rising popularity and increasing scale of information networks, there is a lack of general analytical processing frameworks for exploiting the information contained in the networks. The lack of such frameworks inhibits personalized navigation and interactive knowledge exploration. The work supports the Infonet-OLAP framework by extending methods for structure discovery, network summarizations, and self quality assurance of underlying networks. If successful, the techniques would simplify information network analytical processing and transform existing ad hoc graph exploratory work into a unified framework as traditional OLAP does to multidimensional data analysis.
