Using tagflake for condensing navigable tag hierarchies from tag clouds
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Ontologies of Appropriate Size
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Creating tag hierarchies for effective navigation in social media
Proceedings of the 2008 ACM workshop on Search in social media
Determining Automatically the Size of Learned Ontologies
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Learning subsumption hierarchies of ontology concepts from texts
Web Intelligence and Agent Systems
A system for debugging missing is-a structure in networked ontologies
DILS'10 Proceedings of the 7th international conference on Data integration in the life sciences
Navigating within news collections using tag-flakes
Journal of Visual Languages and Computing
Debugging the missing is-a structure of networked ontologies
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
Phrase pair classification for identifying subtopics
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
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
A PAM-based ontology concept and hierarchy learning method
Journal of Information Science
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This paper proposes a method for learning ontologies given a corpus of text documents. The method identifies concepts in documents and organizes them into a subsumption hierarchy, without presupposing the existence of a seed ontology. The method uncovers latent topics in terms of which document text is being generated. These topics form the concepts of the new ontology. This is done in a language neutral way, using probabilistic space reduction techniques over the original term space of the corpus. Given multiple sets of concepts (latent topics) being discovered, the proposed method constructs a subsumption hierarchy by performing conditional independence tests among pairs of latent topics, given a third one. The paper provides experimental results over the GENIA corpus from the domain of biomedicine.