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» Marking Time in Sequence Mining
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SDM
2009
SIAM
208views Data Mining» more  SDM 2009»
14 years 5 months ago
Topic Evolution in a Stream of Documents.
Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
Alexander Hinneburg, Andrè Gohr, Myra Spili...
DKE
2006
125views more  DKE 2006»
13 years 8 months ago
Online clustering of parallel data streams
In recent years, the management and processing of so-called data streams has become a topic of active research in several fields of computer science such as, e.g., distributed sys...
Jürgen Beringer, Eyke Hüllermeier
GIS
2007
ACM
14 years 2 months ago
Predicting future locations using clusters' centroids
As technology advances we encounter more available data on moving objects, thus increasing our ability to mine spatiotemporal data. We can use this data for learning moving object...
Sigal Elnekave, Mark Last, Oded Maimon
ICDM
2002
IEEE
156views Data Mining» more  ICDM 2002»
14 years 1 months ago
Predicting Rare Events In Temporal Domains
Temporal data mining aims at finding patterns in historical data. Our work proposes an approach to extract temporal patterns from data to predict the occurrence of target events,...
Ricardo Vilalta, Sheng Ma
SIGMOD
2004
ACM
184views Database» more  SIGMOD 2004»
14 years 8 months ago
Identifying Similarities, Periodicities and Bursts for Online Search Queries
We present several methods for mining knowledge from the query logs of the MSN search engine. Using the query logs, we build a time series for each query word or phrase (e.g., `Th...
Michail Vlachos, Christopher Meek, Zografoula Vage...