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PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 4 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 8 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
KDD
2001
ACM
196views Data Mining» more  KDD 2001»
14 years 10 months ago
Efficient discovery of error-tolerant frequent itemsets in high dimensions
We present a generalization of frequent itemsets allowing the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifie...
Cheng Yang, Usama M. Fayyad, Paul S. Bradley
ICDE
1995
IEEE
192views Database» more  ICDE 1995»
14 years 11 months ago
Mining Sequential Patterns
Abstract. The problem of mining sequential patterns was recently introduced in 3 . We are given a database of sequences, where each sequence is a list of transactions ordered by tr...
Rakesh Agrawal, Ramakrishnan Srikant
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 10 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne