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[ACM Press the 2004 ACM SIGKDD international conference - Seattle, WA, USA (2004.08.22-2004.08.25)] Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '04 - Probabilistic author-topic models for information discovery

โœ Scribed by Steyvers, Mark; Smyth, Padhraic; Rosen-Zvi, Michal; Griffiths, Thomas


Book ID
124054324
Publisher
ACM Press
Year
2004
Weight
316 KB
Category
Article

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[ACM Press the 2004 ACM SIGKDD internati
โœ Steyvers, Mark; Smyth, Padhraic; Rosen-Zvi, Michal; Griffiths, Thomas ๐Ÿ“‚ Article ๐Ÿ“… 2004 ๐Ÿ› ACM Press โš– 316 KB

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 process. Each author is represented by a probability distribution over topics, and each topic is represented as a probabilit