Year: 2004
Type: conference-paper
Abstract: We present a novel approach for automatically acquiring English topic signatures. Given a particular concept, or word sense, a topic signature is a set of words that tend to co-occur with it. Topic signatures can be useful in a number of Natural Language Processing (NLP) applications, such as Word Sense Disambiguation (WSD) and Text Summarisation. Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available in corpora and on the Web. We evaluated the topic signatures on a WSD task, where we trained a second-order vector cooccurrence algorithm on standard WSD datasets, with promising results.
Author: Xinglong Wang
Institution: University of Sussex
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Funder: University of Sussex
OpenAlex ID: W2158879790