Style in the Long Tail: Discovering Unique Interests with Latent Variable Models in Large Scale Social E-commerce Diane Hu Rob Hall

Source URL: mimno.infosci.cornell.edu

• Recommender systems
• Social information processing
• Collective intelligence
• Social networking services
• Humancomputer interaction
• Collaborative filtering
• Etsy
• Cold start
• Latent Dirichlet allocation
• Facebook
• GroupLens Research
• Personalization

Topic Modeling Variation across News Sources Gregory Ichneumon Brown ABSTRACT In this project we apply topic models to news articles to infer topics that provide insight into the variation between to

Source URL: greg.ichneumon.net

• Statistical natural language processing
• Statistics
• Probability
• Artificial intelligence
• Topic model
• Latent Dirichlet allocation
• Dirichlet distribution
• Gibbs sampling
• Usenet newsgroup
• News
• Unsupervised learning
• Dynamic topic model

Pragmatic metadata matters: How data about the usage of data effects semantic user models Claudia Wagner1 , Markus Strohmaier2 , and Yulan He3 1

Source URL: claudiawagner.info

• Statistical natural language processing
• Data
• Knowledge representation
• Data management
• Information
• Technical communication
• Records management
• Latent Dirichlet allocation
• Topic model
• Database
• Metadata registry

Jointly Modeling Aspects, Ratings and Sentiments for Movie Recommendation (JMARS) Qiming Diao Minghui Qiu∗

Source URL: www.andrew.cmu.edu

• Statistical natural language processing
• Affective computing
• Natural language processing
• Sentiment analysis
• Recommender system
• Collaborative filtering
• Grammatical aspect
• Latent Dirichlet allocation
• Topic model
• Film criticism
• User review

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis

Source URL: dept.stat.lsa.umich.edu

• Statistics
• Probability
• Statistical natural language processing
• Probability distributions
• Latent Dirichlet allocation
• Topic model
• Mixture model
• Dirichlet distribution
• Normal distribution
• Gibbs sampling
• Statistical inference

Supplementary Material for “Distributed Online Learning for Latent Dirichlet Allocation” JinYeong Bak, Dongwoo Kim and Alice Oh Department of Computer Science Korea Advanced Institute of Science and Technology

Source URL: uilab.kaist.ac.kr

Gaussian LDA for Topic Models with Word Embeddings Rajarshi Das* , Manzil Zaheer* , Chris Dyer School of Computer Science Carnegie Mellon University Pittsburgh, PA, 15213, USA {rajarshd, manzilz, cdyer} @cs.cmu.edu

Source URL: manzil.ml

• Statistics
• Statistical natural language processing
• Machine learning
• Probability
• Latent Dirichlet allocation
• Topic model
• Latent semantic analysis
• Word2vec
• Semantic similarity
• Vector space model
• Word embedding
• Gibbs sampling

Word Features for Latent Dirichlet Allocation James Petterson1, Alex Smola2, Tiberio Caetano1, Wray Buntine1, Shravan Narayanamurthy3 1 NICTA and ANU, Canberra, ACT, Australia 2 Yahoo! Research, Santa Clara, CA, USA

Source URL: tiberiocaetano.com

Immersive Recommendation: News and Event Recommendations Using Personal Digital Traces Cheng-Kang Hsieh Longqi Yang

Source URL: www2016.net

• Software
• Computing
• Digital media
• Social networking services
• Social information processing
• Social media
• Collective intelligence
• Statistical natural language processing
• Recommender system
• Collaborative filtering
• Latent Dirichlet allocation
• Topic model

Hierarchically Supervised Latent Dirichlet Allocation Adler Perotte Nicholas Bartlett No´emie Elhadad

Source URL: www.stat.columbia.edu