183
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KDD
2006
ACM
16 years 7 months ago
2006
ACM
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
196
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
Recent research has identified significant vulnerabilities in recommender systems. Shilling attacks, in which attackers introduce biased ratings in order to influence future recom...
165
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
171
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
Frequent coherent subgraphscan provide valuable knowledgeabout the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large...
193
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
161
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
In many applications, association rules will only be interesting if they represent non-trivial correlations between all constituent items. Numerous techniques have been developed ...
207
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
208
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
183
click to vote
KDD
2006
ACM
16 years 7 months ago
2006
ACM
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...