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» Discovering Predictive Association Rules
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KDD
2004
ACM
135views Data Mining» more  KDD 2004»
14 years 8 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker
CIKM
2004
Springer
14 years 1 months ago
Discovering frequently changing structures from historical structural deltas of unordered XML
Recently, a large amount of work has been done in XML data mining. However, we observed that most of the existing works focus on the snapshot XML data, while XML data is dynamic i...
Qiankun Zhao, Sourav S. Bhowmick, Mukesh K. Mohani...
ICMCS
2010
IEEE
156views Multimedia» more  ICMCS 2010»
13 years 8 months ago
Enriching music mood annotation by semantic association reasoning
Mood annotation of music is challenging as it concerns not only audio content but also extra-musical information. It is a representative research topic about how to traverse the w...
Jun Wang, Xavier Anguera, Xiaoou Chen, Deshun Yang
FSKD
2005
Springer
90views Fuzzy Logic» more  FSKD 2005»
14 years 1 months ago
Direct Candidates Generation: A Novel Algorithm for Discovering Complete Share-Frequent Itemsets
The value of the itemset share is one way of evaluating the magnitude of an itemset. From business perspective, itemset share values reflect more the significance of itemsets for m...
Yu-Chiang Li, Jieh-Shan Yeh, Chin-Chen Chang
FQAS
2004
Springer
146views Database» more  FQAS 2004»
13 years 11 months ago
Discovering Representative Models in Large Time Series Databases
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Simona E. Rombo, Giorgio Terracina