Summary of the paper

Title Constructing a Class-Based Lexical Dictionary using Interactive Topic Models
Authors Kugatsu Sadamitsu, Kuniko Saito, Kenji Imamura and Yoshihiro Matsuo
Abstract This paper proposes a new method of constructing arbitrary class-based related word dictionaries on interactive topic models; we assume that each class is described by a topic. We propose a new semi-supervised method that uses the simplest topic model yielded by the standard EM algorithm; model calculation is very rapid. Furthermore our approach allows a dictionary to be modified interactively and the final dictionary has a hierarchical structure. This paper makes three contributions. First, it proposes a word-based semi-supervised topic model. Second, we apply the semi-supervised topic model to interactive learning; this approach is called the Interactive Topic Model. Third, we propose a score function; it extracts the related words that occupy the middle layer of the hierarchical structure. Experiments show that our method can appropriately retrieve the words belonging to an arbitrary class.
Topics Ontologies, Statistical and machine learning methods, Lexicon, lexical database
Full paper Constructing a Class-Based Lexical Dictionary using Interactive Topic Models
Bibtex @InProceedings{SADAMITSU12.279,
  author = {Kugatsu Sadamitsu and Kuniko Saito and Kenji Imamura and Yoshihiro Matsuo},
  title = {Constructing a Class-Based Lexical Dictionary using Interactive Topic Models},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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