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» Detecting Topic Drift with Compound Topic Models
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CICLING
2010
Springer
14 years 18 days ago
Towards Automatic Detection and Tracking of Topic Change
We present an approach for automatic detection of topic change. Our approach is based on the analysis of statistical features of topics in time-sliced corpora and their dynamics ov...
Florian Holz, Sven Teresniak
SDM
2009
SIAM
208views Data Mining» more  SDM 2009»
14 years 2 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...
KDD
2004
ACM
209views Data Mining» more  KDD 2004»
14 years 6 months ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi
SDM
2007
SIAM
187views Data Mining» more  SDM 2007»
13 years 7 months ago
Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
Arindam Banerjee, Sugato Basu
CVPR
2008
IEEE
14 years 7 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele