Paper: A Comparative Study of Language Models for Book and Author Recognition

ACL ID I05-1084
Title A Comparative Study of Language Models for Book and Author Recognition
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2005
Authors

Linguistic information can help improve evaluation of simi- larity between documents; however, the kind of linguistic information to be used depends on the task. In this paper, we show that distributions of syntactic structures capture the way works are written and accurately identify individual books more than 76% of the time. In comparison, baseline features, e.g., tfidf-weighted keywords, function words, etc., give an accuracy of at most 66%. However, testing the same features on au- thorship attribution shows that distributions of syntactic structures are less successful than function words on this task; syntactic structures vary even among the works of the same author whereas features such as func- tion words are distributed more similarly among the works of an author and can more e...