Latent dirichlet allocation
TLDR
This work proposes a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hofmann's aspect model.Abstract:
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, in turn, modeled as an infinite mixture over an underlying set of topic probabilities. In the context of text modeling, the topic probabilities provide an explicit representation of a document. We present efficient approximate inference techniques based on variational methods and an EM algorithm for empirical Bayes parameter estimation. We report results in document modeling, text classification, and collaborative filtering, comparing to a mixture of unigrams model and the probabilistic LSI model.read more
Citations
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Journal ArticleDOI
Uniting the Tribes: Using Text for Marketing Insight
TL;DR: The authors found that words are part of almost every marketplace interaction, including online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data.
Journal ArticleDOI
The Role of Big Data and Predictive Analytics in Retailing
TL;DR: The paper examines the opportunities in and possibilities arising from big data in retailing, particularly along five major data dimensions—data pertaining to customers, products, time, (geo-spatial) location and channel, with a particular focus on the relevance and uses of Bayesian analysis techniques.
Proceedings Article
News verification by exploiting conflicting social viewpoints in microblogs
TL;DR: This paper discovers conflicting viewpoints in news tweets with a topic model method, and builds a credibility propagation network of tweets linked with supporting or opposing relations that generates the final evaluation result for news.
Journal ArticleDOI
Functional Specialization and Flexibility in Human Association Cortex
B.T. Thomas Yeo,Fenna M. Krienen,Simon B. Eickhoff,Siti N. Yaakub,Peter T. Fox,Randy L. Buckner,Christopher L. Asplund,Michael W. L. Chee +7 more
TL;DR: The association cortex is explored by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions, which contribute to the ability to execute multiple and varied tasks.
Proceedings ArticleDOI
Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams
Jacob Ratkiewicz,Michael Conover,Mark R. Meiss,Bruno Gonçalves,Snehal Patil,Alessandro Flammini,Filippo Menczer +6 more
TL;DR: In this article, the authors introduce an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events.
References
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Indexing by Latent Semantic Analysis
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