The problem of integrating multiple information sources into a uni?ed data store is currently one of the most important challenges in data management. Within the ?eld of source integration, the problem of automatically gen- ating an integrated description of the data sources is surely one of the most relevant. The signi?cance of the issue can be best understood if one c- siders the huge number of information sources that an organization has to integrate. Indeed, it is even impossible to try to do all the work by hand. Like other important issues in data management, the problem of integrating multiple data sources into a unique global system has several facets, each of which represents, “per se”, an interesting research problem, and comprises, for instance, that of recognizing, at the intensional level, similarities and dissimilarities among scheme objects, that of resolving representation m- matches among schemes, and that of deciding how to obtain an integrated data store out of a set of input sources and of a semantic description of their contents. The research and application relevance of such issues has attracted wide interest in the database community in recent years. And, as a con- quence, several techniques have been presented in the literature attacking one side or another of this complex and multifarious problem.

Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Conference on Data Engineering and Management, ICDEM 2010, held in Tiruchirappalli, India, in July 2010. The 46 revised full papers presented together with 1 keynote paper and 2 tutorial papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Digital Library; Knowledge and Mulsemedia; Data Management and Knowledge Extraction; Natural Language Processing; Workshop on Data Mining with Graphs and Matrices.

Computing and communications in colleges and universities.