The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The Journal of Machine Learning Research
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Probabilistic author-topic models for information discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Topic modeling with network regularization
Proceedings of the 17th international conference on World Wide Web
Joint latent topic models for text and citations
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Modeling hidden topics on document manifold
Proceedings of the 17th ACM conference on Information and knowledge management
Effective latent space graph-based re-ranking model with global consistency
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Probabilistic dyadic data analysis with local and global consistency
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
A generalized Co-HITS algorithm and its application to bipartite graphs
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Ranking-based clustering of heterogeneous information networks with star network schema
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Logistic Stick-Breaking Process
The Journal of Machine Learning Research
Probabilistic topic models with biased propagation on heterogeneous information networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
AMETHYST: a system for mining and exploring topical hierarchies of heterogeneous data
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Tag-weighted topic model for mining semi-structured documents
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
The dual-sparse topic model: mining focused topics and focused terms in short text
Proceedings of the 23rd international conference on World wide web
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A nonparametric Bayesian contextual focused topic model (cFTM) is proposed. The cFTM infers a sparse ("focused") set of topics for each document, while also leveraging contextual information about the author(s) and document venue. The hierarchical beta process, coupled with a Bernoulli process, is employed to infer the focused set of topics associated with each author and venue; the same construction is also employed to infer those topics associated with a given document that are unusual (termed "random effects"), relative to topics that are inferred as probable for the associated author(s) and venue. To leverage statistical strength and infer latent interrelationships between authors and venues, the Dirichlet process is utilized to cluster authors and venues. The cFTM automatically infers the number of topics needed to represent the corpus, the number of author and venue clusters, and the probabilistic importance of the author, venue and random-effect information on word assignment for a given document. Efficient MCMC inference is presented. Example results and interpretations are presented for two real datasets, demonstrating promising performance, with comparison to other state-of-the-art methods.