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KDD
2006
ACM
141views Data Mining» more  KDD 2006»
15 years 10 months ago
Statistical entity-topic models
The primary purpose of news articles is to convey information about who, what, when and where. But learning and summarizing these relationships for collections of thousands to mil...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
15 years 10 months ago
Aggregating time partitions
Partitions of sequential data exist either per se or as a result of sequence segmentation algorithms. It is often the case that the same timeline is partitioned in many different ...
Evimaria Terzi, Panayiotis Tsaparas, Taneli Mielik...
KDD
2006
ACM
147views Data Mining» more  KDD 2006»
15 years 10 months ago
Summarizing itemset patterns using probabilistic models
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Chao Wang, Srinivasan Parthasarathy
KDD
2006
ACM
163views Data Mining» more  KDD 2006»
15 years 10 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
KDD
2006
ACM
177views Data Mining» more  KDD 2006»
15 years 10 months ago
Topics over time: a non-Markov continuous-time model of topical trends
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
Xuerui Wang, Andrew McCallum