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ICDM
2006
IEEE
227views Data Mining» more  ICDM 2006»
15 years 3 months ago
Incremental Mining of Sequential Patterns over a Stream Sliding Window
Incremental mining of sequential patterns from data streams is one of the most challenging problems in mining data streams. However, previous work of mining sequential patterns fr...
Chin-Chuan Ho, Hua-Fu Li, Fang-Fei Kuo, Suh-Yin Le...
ICDE
2003
IEEE
148views Database» more  ICDE 2003»
15 years 11 months ago
Dynamic Clustering of Evolving Streams with a Single Pass
Stream data is common in many applications, e.g., stock quotes, merchandize sales record, system logs, etc.. It is of great importance to analyze these stream data. As one of the ...
Jiong Yang
93
Voted
SEMWEB
2010
Springer
14 years 7 months ago
Enabling Ontology-Based Access to Streaming Data Sources
The availability of streaming data sources is progressively increasing thanks to the development of ubiquitous data capturing technologies such as sensor networks. The heterogeneit...
Jean-Paul Calbimonte, Óscar Corcho, Alasdai...
DIS
2010
Springer
14 years 8 months ago
Sentiment Knowledge Discovery in Twitter Streaming Data
Micro-blogs are a challenging new source of information for data mining techniques. Twitter is a micro-blogging service built to discover what is happening at any moment in time, a...
Albert Bifet, Eibe Frank
SSDBM
2007
IEEE
127views Database» more  SSDBM 2007»
15 years 3 months ago
A Fast Algorithm for Approximate Quantiles in High Speed Data Streams
We present a fast algorithm for computing approximate quantiles in high speed data streams with deterministic error bounds. For data streams of size N where N is unknown in advanc...
Qi Zhang, Wei Wang 0010