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» Probabilistic author-topic models for information discovery
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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
10 years 16 days ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
AAAI
2015
3 years 8 months ago
A Probabilistic Model for Bursty Topic Discovery in Microblogs
Bursty topics discovery in microblogs is important for people to grasp essential and valuable information. However, the task is challenging since microblog posts are particularly ...
Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Jun Xu, Xueq...
ICDM
2007
IEEE
133views Data Mining» more  ICDM 2007»
9 years 6 months ago
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Xuerui Wang, Andrew McCallum, Xing Wei
KDD
2008
ACM
257views Data Mining» more  KDD 2008»
10 years 16 days ago
Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
Issei Sato, Minoru Yoshida, Hiroshi Nakagawa
MM
2009
ACM
195views Multimedia» more  MM 2009»
9 years 6 months ago
Flickr hypergroups
The amount of multimedia content available online constantly increases, and this leads to problems for users who search for content or similar communities. Users in Flickr often s...
Radu Andrei Negoescu, Brett Adams, Dinh Q. Phung, ...
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