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Human and machine discovery are gradual problem-solving processes
of searching large problem spaces for incompletely defined goal
objects. Research on problem solving has usually focused on
searching an `instance space' (empirical exploration) and a
`hypothesis space' (generation of theories). In scientific
discovery, searching must often extend to other spaces as well:
spaces of possible problems, of new or improved scientific
instruments, of new problem representations, of new concepts, and
others. This book focuses especially on the processes for finding
new problem representations and new concepts, which are relatively
new domains for research on discovery. Scientific discovery has
usually been studied as an activity of individual investigators,
but these individuals are positioned in a larger social structure
of science, being linked by the `blackboard' of open publication
(as well as by direct collaboration). Even while an investigator is
working alone, the process is strongly influenced by knowledge and
skills stored in memory as a result of previous social
interactions. In this sense, all research on discovery, including
the investigations on individual processes discussed in this book,
is social psychology, or even sociology.
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Principles of Data Mining and Knowledge Discovery - 4th European Conference, PKDD, 2000, Lyon, France, September 13-16, 2000 Proceedings (Paperback, 2000 ed.)
Djamel A. Zighed, Jan Komorowski, Jan Zytkow
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R3,328
Discovery Miles 33 280
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2000, held in Lyon, France in September 2000. The 86 revised papers included in the book correspond to the 29 oral presentations and 57 posters presented at the conference. They were carefully reviewed and selected from 147 submissions. The book offers topical sections on new directions, rules and trees, databases and reward-based learning, classification, association rules and exceptions, instance-based discovery, clustering, and time series analysis.
This book constitutes the refereed proceedings of the Third
European Conference on Principles and Practice of Knowledge
Discovery in Databases, PKDD'99, held in Prague, Czech Republic in
September 1999.
The 28 revised full papers and 48 poster presentations were
carefully reviewed and selected from 106 full papers submitted. The
papers are organized in topical sections on time series,
applications, taxonomies and partitions, logic methods, distributed
and multirelational databases, text mining and feature selection,
rules and induction, and interesting and unusual issues.
This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997.The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.
Human and machine discovery are gradual problem-solving processes
of searching large problem spaces for incompletely defined goal
objects. Research on problem solving has usually focused on
searching an `instance space' (empirical exploration) and a
`hypothesis space' (generation of theories). In scientific
discovery, searching must often extend to other spaces as well:
spaces of possible problems, of new or improved scientific
instruments, of new problem representations, of new concepts, and
others. This book focuses especially on the processes for finding
new problem representations and new concepts, which are relatively
new domains for research on discovery. Scientific discovery has
usually been studied as an activity of individual investigators,
but these individuals are positioned in a larger social structure
of science, being linked by the `blackboard' of open publication
(as well as by direct collaboration). Even while an investigator is
working alone, the process is strongly influenced by knowledge and
skills stored in memory as a result of previous social
interactions. In this sense, all research on discovery, including
the investigations on individual processes discussed in this book,
is social psychology, or even sociology.
|
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