Probabilistic Topic Models for Learning Terminological Ontologies

  title={Probabilistic Topic Models for Learning Terminological Ontologies},
  author={Wei Wang and Payam M. Barnaghi and Andrzej Bargiela},
  journal={IEEE Transactions on Knowledge and Data Engineering},
Probabilistic topic models were originally developed and utilized for document modeling and topic extraction in Information Retrieval. In this paper, we describe a new approach for automatic learning of terminological ontologies from text corpus based on such models. In our approach, topic models are used as efficient dimension reduction techniques, which are able to capture semantic relationships between word-topic and topic-document interpreted in terms of probability distributions. We… CONTINUE READING

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