Artificial Intelligence for Automatic Text Summarization | |
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學年 | 106 |
學期 | 2 |
發表日期 | 2018-07-07 |
作品名稱 | Artificial Intelligence for Automatic Text Summarization |
作品名稱(其他語言) | |
著者 | Min-Yuh Day; Chao-Yu Chen |
作品所屬單位 | |
出版者 | |
會議名稱 | The 2018 IEEE 18th International Conference on Information Reuse and Integration (IEEE IRI 2018) |
會議地點 | Salt Lake City, Utah, USA |
摘要 | Automatic text summarization has played a critical role in helping people obtain key information from increasing huge data with the advantaged development of technology. In the past, few literatures are related to solve the problem of generating titles (short summaries) by using artificial intelligence (AI). The purpose of this study is that we proposed an AI approach for automatic text summarization. We developed an AI text summarization system architecture with three models, namely, statistical model, machine learning model, and deep learning model as well as evaluating the performance of three models. Essay titles and essay abstracts are used to train artificial intelligence deep learning model to generate the candidate titles and evaluated by ROUGE for performance evaluation. The contribution of this paper is that we proposed an AI automatic text summarization system by applying deep learning to generate short summaries from the titles and abstracts of the Web of Science (WOS) database. |
關鍵字 | Artificial Intelligence;Sequence-to-Sequence;Automatic Text Summarization, Long Short-Term Memory;Recurrent Neural Network |
語言 | en_US |
收錄於 | |
會議性質 | 國際 |
校內研討會地點 | 無 |
研討會時間 | 20180707~20180709 |
通訊作者 | |
國別 | USA |
公開徵稿 | |
出版型式 | |
出處 | Proceedings of the 2018 IEEE 18th International Conference on Information Reuse and Integration (IEEE IRI 2018) |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115253 ) |