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EDBT
2008
ACM
160views Database» more  EDBT 2008»
10 years 4 months ago
Taxonomy-superimposed graph mining
New graph structures where node labels are members of hierarchically organized ontologies or taxonomies have become commonplace in different domains, e.g., life sciences. It is a ...
Ali Cakmak, Gultekin Özsoyoglu
KDD
2010
ACM
240views Data Mining» more  KDD 2010»
10 years 6 months ago
Diagnosing memory leaks using graph mining on heap dumps
Memory leaks are caused by software programs that prevent the reclamation of memory that is no longer in use. They can cause significant slowdowns, exhaustion of available storag...
Evan K. Maxwell, Godmar Back, Naren Ramakrishnan
DIS
2007
Springer
10 years 6 months ago
Time and Space Efficient Discovery of Maximal Geometric Graphs
A geometric graph is a labeled graph whose vertices are points in the 2D plane with an isomorphism invariant under geometric transformations such as translation, rotation, and scal...
Hiroki Arimura, Takeaki Uno, Shinichi Shimozono
PAKDD
2010
ACM
203views Data Mining» more  PAKDD 2010»
10 years 7 months ago
Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph
Both itemset mining and graph mining have been studied independently. Here, we introduce a novel data structure, which is an unweighted graph whose vertices contain itemsets. From ...
Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun S...
PKDD
2004
Springer
147views Data Mining» more  PKDD 2004»
10 years 8 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...
KES
2004
Springer
10 years 8 months ago
Consumer Behavior Analysis by Graph Mining Technique
In this paper we discuss how graph mining system is applied to sales transaction data so as to understand consumer behavior. First, existing research of consumer behavior analysis ...
Katsutoshi Yada, Hiroshi Motoda, Takashi Washio, A...
DIS
2004
Springer
10 years 8 months ago
Predictive Graph Mining
Abstract. Graph mining approaches are extremely popular and effective in molecular databases. The vast majority of these approaches first derive interesting, i.e. frequent, patte...
Andreas Karwath, Luc De Raedt
MLG
2007
Springer
10 years 9 months ago
Graphs, Hypergraphs, and Inductive Logic Programming
Abstract. There are many connections between graph mining and inductive logic programming (ILP), or more generally relational learning. Up till now these connections have mostly be...
Hendrik Blockeel, Tijn Witsenburg, Joost N. Kok
ADC
2008
Springer
110views Database» more  ADC 2008»
10 years 9 months ago
Graph Mining based on a Data Partitioning Approach
Existing graph mining algorithms typically assume that the dataset can fit into main memory. As many large graph datasets cannot satisfy this condition, truly scalable graph minin...
Son N. Nguyen, Maria E. Orlowska, Xue Li
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