Experiments with latent semantic analysis for word tagging

Authors:
Ashraf Anwar
Affiliations:
Computer Science Department, Gulf University for Science and Technology, Hawalli, Kuwait
Venue:
CSECS'06 Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing
Year:
2006

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Abstract

In this paper I show the possible use of Latent Semantic Analysis (LSA) as an aid for word tagging and ambiguity resolution for words in test sentences. The idea is to use large corpora of training sentences, previously tagged by a human expert; for building an LSA "engine" that is used to aid in tagging future test sentences. Various training and testing phases were done. The results show that LSA seems to do somewhat fair; compared to other statistical word tagging and ambiguity resolution methods. However, there is one main drawback for this approach; the accuracy of word tagging depends on the training corpus.