Title :
Graph-based model for lexical category acquisition
Author :
Zhang, Bichuan ; Wang, Xiaojie ; Fang, Guannan
Author_Institution :
Center for Intell. Sci. & Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
We present a novel approach for discovering word categories, sets of words sharing a significant aspect of distributional context. We determine symmetric similarity of word pair, lexical category is then created based on graph-partitioning method. We train our model on a corpus of child-directed speech from CHILDES and show that the model successful learns word categories. Furthermore, a number of different measures have been proposed for evaluating computational models of category acquisition. In this paper, we propose a new measure that meets three criteria: informativeness, diversity and purity.
Keywords :
grammars; graph theory; CHILDES; child-directed speech corpus; distributional context aspect; diversity criteria; graph-based model; graph-partitioning method; informativeness criteria; lexical category acquisition; purity criteria; word category discovery; word pair symmetric similarity; Computational modeling; Context; Context modeling; Educational institutions; Semantics; Speech; Syntactics; CHILDES; Evaluation metric; Graph-based; Lexical category acquisition;
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
DOI :
10.1109/ISRA.2012.6219167