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PKDD
2004
Springer
97views Data Mining» more  PKDD 2004»
9 years 9 months ago
Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources
Attribute noise can affect classification learning. Previous work in handling attribute noise has focused on those predictable attributes that can be predicted by the class and o...
Ying Yang, Xindong Wu, Xingquan Zhu
PKDD
2004
Springer
105views Data Mining» more  PKDD 2004»
9 years 9 months ago
Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators
Xin Wang, Camilo Rostoker, Howard J. Hamilton
PKDD
2004
Springer
168views Data Mining» more  PKDD 2004»
9 years 9 months ago
Combining Winnow and Orthogonal Sparse Bigrams for Incremental Spam Filtering
Spam filtering is a text categorization task that has attracted significant attention due to the increasingly huge amounts of junk email on the Internet. While current best-pract...
Christian Siefkes, Fidelis Assis, Shalendra Chhabr...
PKDD
2004
Springer
131views Data Mining» more  PKDD 2004»
9 years 9 months ago
Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
PKDD
2004
Springer
102views Data Mining» more  PKDD 2004»
9 years 9 months ago
Improving the Performance of the RISE Algorithm
Ideally, a multi-strategy learning algorithm performs better than its component approaches. RISE is a multi-strategy algorithm that combines rule induction and instance-based learn...
Aloísio Carlos de Pina, Gerson Zaverucha
PKDD
2004
Springer
144views Data Mining» more  PKDD 2004»
9 years 9 months ago
SEWeP: A Web Mining System Supporting Semantic Personalization
We present SEWeP, a Web Personalization prototype system that integrates usage data with content semantics, expressed in taxonomy terms, in order to produce a broader yet semantica...
Stratos Paulakis, Charalampos Lampos, Magdalini Ei...
PKDD
2004
Springer
147views Data Mining» more  PKDD 2004»
9 years 9 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...
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