| Автор | VAN DE CRUYS, TIM |
| Дата выпуска | 2010 |
| dc.description | AbstractThe distributional similarity methods have proven to be a valuable tool for the induction of semantic similarity. Until now, most algorithms use two-way co-occurrence data to compute the meaning of words. Co-occurrence frequencies, however, need not be pairwise. One can easily imagine situations where it is desirable to investigate co-occurrence frequencies of three modes and beyond. This paper will investigate tensor factorization methods to build a model of three-way co-occurrences. The approach is applied to the problem of selectional preference induction, and automatically evaluated in a pseudo-disambiguation task. The results show that tensor factorization, and non-negative tensor factorization in particular, is a promising tool for Natural Language Processing (nlp). |
| Формат | application.pdf |
| Издатель | Cambridge University Press |
| Копирайт | Copyright © Cambridge University Press 2010 |
| Название | A non-negative tensor factorization model for selectional preference induction |
| Тип | research-article |
| DOI | 10.1017/S1351324910000148 |
| Electronic ISSN | 1469-8110 |
| Print ISSN | 1351-3249 |
| Журнал | Natural Language Engineering |
| Том | 16 |
| Первая страница | 417 |
| Последняя страница | 437 |
| Аффилиация | VAN DE CRUYS TIM; INRIA & Université Paris 7, Rocquencourt, France e-mail: timvdc@gmail.com |
| Выпуск | 4 |
