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Author Clark, Alexander ♦ Tim, Issco
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Rare Word ♦ Morphological Information ♦ Unlabelled Text ♦ Speech Induction ♦ Wide Range ♦ Unsupervised Algorithm
Description In Proceedings of the 10th Conference of the European Chapter of the Association for Computational Linguistics
In this paper we discuss algorithms for clustering words into classes from unlabelled text using unsupervised algorithms, based on distributional and morphological information. We show how the use of morphological information can improve the performance on rare words, and that this is robust across a wide range of languages. 1
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2003-01-01