CfPapers: IEEE TDKE Special Issue on Learning&Discovery in K-B DBs
Date: Sun, 23 Feb 1992 21:54:09 GMT
Message-ID: <1992Feb23.215409.2051_at_sfu.ca>
Subject: CFPapers: IEEE TDKE Special Issue on Learning & Discovery in K-B DBs
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Call For Papers IEEE Transactions on Knowledge and Data Engineering Special Issue on Learning and Discovery in Knowledge-Based Databases
The effective and efficient use of intelligent information systems requires far better tools and techniques which can assist a wide range of users to create, comprehend, modify, and otherwise use such systems. Full use of future intelligent information systems will be impossible without such aids. Inextricably intertwined with the rapid growth of data and information available, techniques which extract knowledge from databases must be developed. Techniques developed from machine learning theory are not readily amenable to database technology without modification; databases are rapidly changing in response to new opportunitieshence the development of knowledge-based and object oriented paradigms. As one noted researcher has put it, "Computers have promised us a fountain of wisdom, but they have delivered a flood of information." Recent research progress, coupled with reported application successes, has created a significant interest in learning and discovery in Knowledge-Based Databases.
The guest editors solicit contributions for this Special Issue of TKDE in the following areas:
- Learning and Discovery in Databases
- Integration of Knowledge-based and Object-Oriented Approaches
- Data Engineering Tools and Techniques for Learning and Discovery in Databases
- Visual and Perceptual ways of Discovery in Data
- Integration of Knowledge-based and Statistical Approaches
- Integration of Different Discovery and/or Learning Methods
- Use of Domain Knowledge in Discovery and Re-use of Discovered Knowledge
- Learning and Discovery of Causal Structure in Data
- Interactive Systems for Data Exploration and Discovery
- High-level Query Answering and Data Summarization
- Discovery in Complex Data or Text
- Ethics of Discovery in Social Databases
- Successful Applications in Medicine, Business and other areas.
Manuscripts should be no more than 25 typewritten, double spaced pages, including figures and references. Each manuscript should have a title page with the title of the paper, full name(s) and affiliation(s) of author(s), complete postal and electronic addresses, telephone number(s), and informative 150-200 word abstract and a list of identifying keywords.
Please submit 6 copies of a paper to the guest editors by 15 June 1992.
Nick Cercone/Mas Tsuchiya Special Issue of IEEE TDKE Centre for Systems Science Simon Fraser University Burnaby, British Columbia Canada V5A 1S6
Acceptance status letters will be sent by 1 November 1992.
Received on Sun Feb 23 1992 - 22:54:09 CET