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» On Granular Knowledge Structures
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KR
2004
Springer
15 years 6 months ago
Knowledge Discovery by Reversing Inductive Knowledge Representation
In a very basic sense, the aim of knowledge discovery is to reveal structures of knowledge which can be seen as being represented by structural relationships. In this paper, we ma...
Gabriele Kern-Isberner, Jens Fisseler
121
Voted
AMKM
2003
Springer
15 years 6 months ago
Discovering, Visualizing, and Sharing Knowledge through Personalized Learning Knowledge Maps
This paper presents an agent-based approach to semantic exploration and knowledge discovery in large information spaces by means of capturing, visualizing and making usable implic...
Jasminko Novak, Michael Wurst, Monika Fleischmann,...
116
Voted
DASFAA
2006
IEEE
152views Database» more  DASFAA 2006»
15 years 6 months ago
Effective Keyword Search in XML Documents Based on MIU
Keyword search is an effective approach for most users to search for information because they do not need to learn complex query languages or the underlying structures of the data....
Jianjun Xu, Jiaheng Lu, Wei Wang 0009, Baile Shi
136
Voted
IEAAIE
2005
Springer
15 years 6 months ago
Analyzing Multi-level Spatial Association Rules Through a Graph-Based Visualization
Association rules discovery is a fundamental task in spatial data mining where data are naturally described at multiple levels of granularity. ARES is a spatial data mining system ...
Annalisa Appice, Paolo Buono
87
Voted
CSDA
2006
72views more  CSDA 2006»
15 years 22 days ago
Generalized theory of uncertainty (GTU) - principal concepts and ideas
Uncertainty is an attribute of information. The path-breaking work of Shannon has led to a universal acceptance of the thesis that information is statistical in nature. Concomitan...
Lotfi A. Zadeh