The Journal of Machine Learning Research
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Pachinko allocation: DAG-structured mixture models of topic correlations
ICML '06 Proceedings of the 23rd international conference on Machine learning
Topic modeling: beyond bag-of-words
ICML '06 Proceedings of the 23rd international conference on Machine learning
Modeling online reviews with multi-grain topic models
Proceedings of the 17th international conference on World Wide Web
Latent dirichlet allocation based multi-document summarization
Proceedings of the second workshop on Analytics for noisy unstructured text data
Learning Ontologies of Appropriate Size
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Combining concept hierarchies and statistical topic models
Proceedings of the 17th ACM conference on Information and knowledge management
Mining common topics from multiple asynchronous text streams
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Refined experts: improving classification in large taxonomies
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Exploiting social context for expertise propagation
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A Generic Approach to Topic Models
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Multi-grain hierarchical topic extraction algorithm for text mining
Expert Systems with Applications: An International Journal
Estimating Likelihoods for Topic Models
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Cross-cultural analysis of blogs and forums with mixed-collection topic models
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Large-scale hierarchical text classification without labelled data
Proceedings of the fourth ACM international conference on Web search and data mining
Ontology population and enrichment: state of the art
Knowledge-driven multimedia information extraction and ontology evolution
Discovery of topically coherent sentences for extractive summarization
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Multiple domain user personalization
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Entity disambiguation with hierarchical topic models
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Typology of mixed-membership models: towards a design method
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes
The Journal of Machine Learning Research
Cross-cutting models of lexical semantics
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Hierarchical classification of web documents by stratified discriminant analysis
IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
Shared components topic models
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Modelling selectional preferences in a lexical hierarchy
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
A joint model for discovery of aspects in utterances
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
SSHLDA: a semi-supervised hierarchical topic model
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Document-topic hierarchies from document graphs
Proceedings of the 21st ACM international conference on Information and knowledge management
Modeling topic hierarchies with the recursive chinese restaurant process
Proceedings of the 21st ACM international conference on Information and knowledge management
Hierarchical topic integration through semi-supervised hierarchical topic modeling
Proceedings of the 21st ACM international conference on Information and knowledge management
A phrase mining framework for recursive construction of a topical hierarchy
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Content coverage maximization on word networks for hierarchical topic summarization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
A hierarchical Dirichlet model for taxonomy expansion for search engines
Proceedings of the 23rd international conference on World wide web
Hi-index | 0.00 |
The four-level pachinko allocation model (PAM) (Li & McCallum, 2006) represents correlations among topics using a DAG structure. It does not, however, represent a nested hierarchy of topics, with some topical word distributions representing the vocabulary that is shared among several more specific topics. This paper presents hierarchical PAM---an enhancement that explicitly represents a topic hierarchy. This model can be seen as combining the advantages of hLDA's topical hierarchy representation with PAM's ability to mix multiple leaves of the topic hierarchy. Experimental results show improvements in likelihood of held-out documents, as well as mutual information between automatically-discovered topics and humangenerated categories such as journals.