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» Accounting for burstiness in topic models
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SIGIR
2002
ACM
13 years 5 months ago
A critical examination of TDT's cost function
Topic Detection and Tracking (TDT) tasks are evaluated using a cost function. The standard TDT cost function assumes a constant probability of relevance P(rel) across all topics. ...
R. Manmatha, Ao Feng, James Allan
ACL
2012
11 years 7 months ago
A Novel Burst-based Text Representation Model for Scalable Event Detection
Mining retrospective events from text streams has been an important research topic. Classic text representation model (i.e., vector space model) cannot model temporal aspects of d...
Xin Zhao, Rishan Chen, Kai Fan, Hongfei Yan, Xiaom...
ACML
2009
Springer
13 years 12 months ago
Injecting Structured Data to Generative Topic Model in Enterprise Settings
Enterprises have accumulated both structured and unstructured data steadily as computing resources improve. However, previous research on enterprise data mining often treats these ...
Han Xiao, Xiaojie Wang, Chao Du
KDD
2007
ACM
237views Data Mining» more  KDD 2007»
14 years 5 months ago
Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior
Documents, such as those seen on Wikipedia and Folksonomy, have tended to be assigned with multiple topics as a meta-data. Therefore, it is more and more important to analyze a re...
Issei Sato, Hiroshi Nakagawa
CIKM
2008
Springer
13 years 7 months ago
Topic models and a revisit of text-related applications
Topic models such as aspect model or LDA have been shown as a promising approach for text modeling. Unlike many previous models that restrict each document to a single topic, topi...
Viet Ha-Thuc, Padmini Srinivasan