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» Mining Frequent Itemsets Using Genetic Algorithm
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IFIP12
2007
14 years 11 months ago
Clustering Improves the Exploration of Graph Mining Results
Mining frequent subgraphs is an area of research where we have a given set of graphs, and where we search for (connected) subgraphs contained in many of these graphs. Each graph ca...
Edgar H. de Graaf, Joost N. Kok, Walter A. Kosters
KES
2007
Springer
14 years 9 months ago
Dynamic route planning for car navigation systems using virus genetic algorithms
This paper describes a practical dynamic route planning method using real road maps in a wide area. The maps include traffic signals, road classes, and the number of lanes. The pr...
Hitoshi Kanoh
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
15 years 3 months ago
Adding Semantics to Email Clustering
This paper presents a novel algorithm to cluster emails according to their contents and the sentence styles of their subject lines. In our algorithm, natural language processing t...
Hua Li, Dou Shen, Benyu Zhang, Zheng Chen, Qiang Y...
PKDD
2004
Springer
147views Data Mining» more  PKDD 2004»
15 years 3 months ago
Using a Hash-Based Method for Apriori-Based Graph Mining
The problem of discovering frequent subgraphs of graph data can be solved by constructing a candidate set of subgraphs first, and then, identifying within this candidate set those...
Phu Chien Nguyen, Takashi Washio, Kouzou Ohara, Hi...
CEC
2007
IEEE
15 years 1 months ago
Mining association rules from databases with continuous attributes using genetic network programming
Most association rule mining algorithms make use of discretization algorithms for handling continuous attributes. Discretization is a process of transforming a continuous attribute...
Karla Taboada, Eloy Gonzales, Kaoru Shimada, Shing...