文章基本信息

标题：Extraction of Paraphrases using Time Series Deep Learning Method
本地全文：下载
作者：Ryuichi Omi ; Yoko Nishihara ; Ryosuke Yamanishi 等
期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2019
卷号：2239
页码：276-278
出版社：Newswood and International Association of Engineers
摘要：We propose a new method to extract paraphrases of inappropriate expressions using long short-term memory (LSTM) as one of the time series deep learning methods. Inappropriate expressions are often described indirectly. To extract inappropriate expressions described indirectly, the meanings of expressions must be identified. The meanings of expressions may vary depending on the domain and context where the expressions are used. The proposed method uses LSTM to learn the series of responses on thread on a bulletin board system. LSTM obtains a model for detecting responses containing inappropriate expressions. When the model evaluates a response as inappropriate, the method extracts words from the response. If a word appears frequently in responses evaluated as inappropriate, the method evaluates the word as a paraphrase for an inappropriate expression. We conducted preliminary experiments. It was confirmed that the method could extract paraphrases for inappropriate expressions.
关键词：Paraphrases for inappropriate expressions; Time series deep learning; Bulletin board system; Word vector with distributed representation