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» Challenges to information systems: time to change
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KDD
1995
ACM
85views Data Mining» more  KDD 1995»
15 years 1 months ago
Estimating the Robustness of Discovered Knowledge
This paper introduces a new measurement, robustness, to measure the quality of machine-discovered knowledge from real-world databases that change over time. A piece of knowledge i...
Chun-Nan Hsu, Craig A. Knoblock
HICSS
1994
IEEE
149views Biometrics» more  HICSS 1994»
15 years 2 months ago
Stochastic Problem Solving by Local Computation Based on Self-Organization Paradigm
We are developing a new problem-solving methodology based on a self-organization paradigm. To realize our future goal of self-organizing computational systems, we have to study co...
Yasusi Kanada, Masao Hirokawa
C3S2E
2009
ACM
15 years 1 months ago
The promise of solid state disks: increasing efficiency and reducing cost of DBMS processing
Most database systems (DBMSs) today are operating on servers equipped with magnetic disks. In our contribution, we want to motivate the use of two emerging and striking technologi...
Karsten Schmidt 0002, Yi Ou, Theo Härder
SIGMOD
2011
ACM
219views Database» more  SIGMOD 2011»
14 years 23 days ago
Context-sensitive ranking for document retrieval
We study the problem of context-sensitive ranking for document retrieval, where a context is defined as a sub-collection of documents, and is specified by queries provided by do...
Liang Jeff Chen, Yannis Papakonstantinou
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 3 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang