Data Mining and Reverse Engineering: Searching for semantics. IFIP TC2 WG2.6 IFIP Seventh Conference on Database Semantics (DS-7) 7–10 October 1997, Leysin, Switzerland(IFIP Advances in Information and Communication Technology)

Today's database engineers are committed to the reuse of existing data, for performance and economic reasons. Moreover, they often have to complement enterprise data with data from external sources, where the corresponding semantics are rarely fully available. Accessing data via the Web is just an example of input from external autonomous repositories. Unfortunately, some database design processes neglect to properly record the initial specifications - because most of the intended semantics are not available anymore. As a consequence, both database researchers and practitioners are facing the issues involved in the discovery and understanding of the semantics hidden in whatever is available: data sets, data stores formats, database schemes, application programs, documentation, metadaa, forms and interviews. This volume focuses on the above issues from the perspective of database semantics, discussing theories, principles, models, methods, formalisms experiences, tools and prototypes for recovering, representing and organizing semantic information on application data from any possible source. This includes in particular the processes known as: data mining and knowledge acquisition/discovery; data reverse engineering; extraction of semantic information from programs; semantic elicitation and visualization; cooperative elaboration of semantics; automatic indexing, classification and clustering; languages and interfaces for data mining or reverse engineering; advanced query models; visual mining; and correspondence investigation in schema integration. This work should be of interest to computer professionals; academic researchers in the area of database management, information retrieval and information systems; and R&D students in computer science.

Table of Contents:
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.