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» Mining data streams: a review
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SIGKDD
2008
125views more  SIGKDD 2008»
13 years 8 months ago
Incremental pattern discovery on streams, graphs and tensors
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
Jimeng Sun
BIODATAMINING
2008
178views more  BIODATAMINING 2008»
13 years 9 months ago
Clustering-based approaches to SAGE data mining
Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical appli...
Haiying Wang, Huiru Zheng, Francisco Azuaje
ICDE
2010
IEEE
198views Database» more  ICDE 2010»
14 years 2 months ago
Power-aware data analysis in sensor networks
Abstract— Sensor networks have evolved to a powerful infrastructure component for event monitoring in many application scenarios. In addition to simple filter and aggregation op...
Daniel Klan, Katja Hose, Marcel Karnstedt, Kai-Uwe...
ICDM
2003
IEEE
238views Data Mining» more  ICDM 2003»
14 years 2 months ago
Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques
We present Sentiment Analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents. Instead of classifying the sentiment of an entire document abou...
Jeonghee Yi, Tetsuya Nasukawa, Razvan C. Bunescu, ...
IS
2008
13 years 8 months ago
Continuous subspace clustering in streaming time series
Performing data mining tasks in streaming data is considered a challenging research direction, due to the continuous data evolution. In this work, we focus on the problem of clust...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...