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» Using and Learning Semantics in Frequent Subgraph Mining
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PKDD
2010
Springer
127views Data Mining» more  PKDD 2010»
14 years 9 months ago
Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs
Defect localisation is essential in software engineering and is an important task in domain-specific data mining. Existing techniques building on call-graph mining can localise dif...
Frank Eichinger, Klaus Krogmann, Roland Klug, Klem...
IDA
2007
Springer
14 years 11 months ago
Inference of node replacement graph grammars
Graph grammars combine the relational aspect of graphs with the iterative and recursive aspects of string grammars, and thus represent an important next step in our ability to dis...
Jacek P. Kukluk, Lawrence B. Holder, Diane J. Cook
DAWAK
2005
Springer
15 years 5 months ago
A Decremental Algorithm for Maintaining Frequent Itemsets in Dynamic Databases
Data mining and machine learning must confront the problem of pattern maintenance because data updating is a fundamental operation in data management. Most existing data-mining alg...
Shichao Zhang, Xindong Wu, Jilian Zhang, Chengqi Z...
ICML
2007
IEEE
16 years 14 days ago
Entire regularization paths for graph data
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda
BIBE
2007
IEEE
141views Bioinformatics» more  BIBE 2007»
15 years 3 months ago
Graph and Topological Structure Mining on Scientific Articles
In this paper, we investigate a new approach for literature mining. We use frequent subgraph mining, and its generalization topological structure mining, for finding interesting re...
Fan Wang, Ruoming Jin, Gagan Agrawal, Helen Piontk...