Data Mining and Reverse Engineering: Searching for Semantics. Ifip Tc2 Wg2.6 Ifip Seventh Conference on Database Semantics (Ds-7) 7-10 October 1997, L

Spaccapietra, Stefano|Maryanski, Fred

ISBN 10: 0412822504 / ISBN 13: 9780412822506

Published by Springer US, 1998

About this Item

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.

Seller Inventory # 458435453

Bibliographic Details

• Title: Data Mining and Reverse Engineering: Searching for Semantics. Ifip Tc2 Wg2.6 Ifip Seventh Conference on Database Semantics (Ds-7) 7-10 October 1997, L
• Publisher: Springer US
• Publication Date: 1998
• Language: English
• ISBN 10: 0412822504
• ISBN 13: 9780412822506
• Binding: Hardcover
• Condition: New
• Seller catalogs:
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Synopsis

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.

Synopsis

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.