{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T13:22:14Z","timestamp":1742390534532},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2002,6,17]],"date-time":"2002-06-17T00:00:00Z","timestamp":1024272000000},"content-version":"unspecified","delay-in-days":108,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nat. Lang. Eng."],"published-print":{"date-parts":[[2002,3]]},"abstract":"<jats:p>We address the problem of clustering words (or constructing a thesaurus) based on co-occurrence \ndata, and conducting syntactic disambiguation by using the acquired word classes. \nWe view the clustering problem as that of estimating a class-based probability distribution \nspecifying the joint probabilities of word pairs. We propose an efficient algorithm based on the \nMinimum Description Length (MDL) principle for estimating such a probability model. Our \nclustering method is a natural extension of that proposed in Brown, Della Pietra, deSouza, \nLai and Mercer (1992). We next propose a syntactic disambiguation method which combines \nthe use of automatically constructed word classes and that of a hand-made thesaurus. The \noverall disambiguation accuracy achieved by our method is 88.2%, which compares favorably \nagainst the accuracies obtained by the state-of-the-art disambiguation methods.<\/jats:p>","DOI":"10.1017\/s1351324902002838","type":"journal-article","created":{"date-parts":[[2002,7,28]],"date-time":"2002-07-28T23:18:00Z","timestamp":1027898280000},"page":"25-42","source":"Crossref","is-referenced-by-count":21,"title":["Word clustering and disambiguation based on co-occurrence data"],"prefix":"10.1017","volume":"8","author":[{"given":"HANG","family":"LI","sequence":"first","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2002,6,17]]},"container-title":["Natural Language Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1351324902002838","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,3,30]],"date-time":"2019-03-30T18:58:28Z","timestamp":1553972308000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1351324902002838\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2002,3]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2002,3]]}},"alternative-id":["S1351324902002838"],"URL":"https:\/\/doi.org\/10.1017\/s1351324902002838","relation":{},"ISSN":["1351-3249","1469-8110"],"issn-type":[{"value":"1351-3249","type":"print"},{"value":"1469-8110","type":"electronic"}],"subject":[],"published":{"date-parts":[[2002,3]]}}}