Data Mining and Reverse Engineering

Searching for Semantics: Data Mining, Reverse Engineering Stefano Spaccapietra Fred M aryanski Swiss Federal Institute of Technology University of Connecticut Lausanne, Switzerland Storrs, CT, USA REVIEW AND FUTURE DIRECTIONS In the last few years, database semantics research has turned sharply from a highly theoretical domain to one with more focus on practical aspects. The DS- 7 Working Conference held in October 1997 in Leysin, Switzerland, demon strated the more pragmatic orientation of the current generation of leading researchers. The papers presented at the meeting emphasized the two major areas: the discovery of semantics and semantic data modeling. The work in the latter category indicates that although object-oriented database management systems have emerged as commercially viable prod ucts, many fundamental modeling issues require further investigation. Today's object-oriented systems provide the capability to describe complex objects and include techniques for mapping from a relational database to objects. However, we must further explore the expression of information regarding the dimensions of time and space. Semantic models possess the richness to describe systems containing spatial and temporal data. The challenge of in corporating these features in a manner that promotes efficient manipulation by the subject specialist still requires extensive development.

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Today's database engineers are committed to the reuse of data, for performance and economic reasons. Moreover, they often have to complement enterprise data with data from external sources, where the corresponding semantics is rarely fully available. As a consequence, both database researchers and practitioners are facing salient issues in the discovery and understanding of the semantics hidden in various forms of external sources: data sets, data stores formats, database schemes, application programs, documentation etc. This book focuses on such issues from the perspective of database semantics, discussing theories, principles and models for recovering, representing and organizing semantic information on application data.

Contenu
One Invited Talks.- 1 OLAP mining: an integration of OLAP with data mining.- 2 Semantic approaches to structuring and querying web sites.- 3 Text mining: natural language techniques for text mining applications.- Two Data Mining.- 4 Improvements in supervised BRAINNE: a method for symbolic data mining using neural networks.- 5 CE: the classifier-estimator framework for data mining.- 6 An associative search method based on symbolic filtering and semantic ordering for database systems.- Three Reverse Engineering.- 7 Contribution to the reverse engineering of OO applications: methodology and case study.- 8 Searching for semantics in COBOL legacy applications.- 9 The reengineering of relational databases based on key and data correlations.- Four Query Languages.- 10 A formalization of ODMG queries.- 11 A metaphorical and visual language for querying an existing relational database.- Five Web Environment.- 12 OFAHIR: 'On-the-Fly' automatic authoring of hypertexts for information retrieval.- 13 TopiCA: a semantic framework for landscaping the information space in federated digital libraries.- 14 Incorporating generalized quantifiers into description logic for representing data source contents.- Six Constraints.- 15 Managing constraint violations in administrative information systems.- 16 Automatic generation of update rules to enforce consistency constraints in design databases.- Seven Database integration.- 17 Discovering and reconciling semantic conflicts: a data mining perspective.- 18 Experience with a combined approach to attribute-matching across heterogeneous databases.- Eight Spatio-Temporal Databases.- 19 Design patterns for spatio-temporal processes.- 20 Modeling and implementation of temporal aspects of objects in commercial information systems.- Index ofcontributors.- Keyword index.