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TEC
2008
104views more  TEC 2008»
13 years 10 months ago
Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy
Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data i...
Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-...
MOBIDE
2010
ACM
13 years 10 months ago
Using data mining to handle missing data in multi-hop sensor network applications
A sensor's data loss or corruption, aka sensor data missing, is a common phenomenon in modern wireless sensor networks. It is more severe for multi-hop sensor network (MSN) a...
Le Gruenwald, Hanqing Yang, Md. Shiblee Sadik, Rah...
ISI
2008
Springer
13 years 10 months ago
Visual Analytics for Supporting Entity Relationship Discovery on Text Data
To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant ...
Hanbo Dai, Ee-Peng Lim, Hady Wirawan Lauw, HweeHwa...
ICCS
2004
Springer
14 years 3 months ago
Iceberg Query Lattices for Datalog
In this paper we study two orthogonal extensions of the classical data mining problem of mining association rules, and show how they naturally interact. The first is the extension...
Gerd Stumme
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
14 years 1 months ago
A framework for specifying explicit bias for revision of approximate information extraction rules
Information extraction is one of the most important techniques used in Text Mining. One of the main problems in building information extraction (IE) systems is that the knowledge ...
Ronen Feldman, Yair Liberzon, Binyamin Rosenfeld, ...