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» Compression-based data mining of sequential data
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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 9 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
KDD
2010
ACM
218views Data Mining» more  KDD 2010»
14 years 16 days ago
Online multiscale dynamic topic models
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, N...
PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
14 years 3 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
SAC
2004
ACM
14 years 2 months ago
A new algorithm for gap constrained sequence mining
The sequence mining problem consists in finding frequent sequential patterns in a database of time-stamped events. Several application domains require limiting the maximum tempor...
Salvatore Orlando, Raffaele Perego, Claudio Silves...
APWEB
2006
Springer
14 years 12 days ago
An Effective System for Mining Web Log
The WWW provides a simple yet effective media for users to search, browse, and retrieve information in the Web. Web log mining is a promising tool to study user behaviors, which co...
Zhenglu Yang, Yitong Wang, Masaru Kitsuregawa