教師資料查詢 | 類別: 會議論文 | 教師: 戴敏育 Min-Yuh Day (瀏覽個人網頁)

標題:A Study on Machine Learning for Imbalanced Datasets with Answer Validation of Question Answering
學年104
學期2
發表日期2016/07/28
作品名稱A Study on Machine Learning for Imbalanced Datasets with Answer Validation of Question Answering
作品名稱(其他語言)
著者Min-Yuh Day; Cheng-Chia Tsai
作品所屬單位
出版者
會議名稱2016 IEEE 17th International Conference on Information Reuse and Integration (IEEE IRI 2016)
會議地點Pittsburgh, Pennsylvania, USA
摘要Question Answering is a system that can process and answer a given question. In recent years, an enormous number of studies have been made on question answering; little is known about the effects of imbalanced datasets with answer validation of question answer system. The objective of this paper is to provide a better understanding of the effects of imbalanced datasets model for answer validation in a real world university entrance exam question answering system. In this paper, we proposed a question answer system and provided a comprehensive analysis of imbalanced datasets and balanced datasets model with Answer Validation of Question Answering system using NTCIR-12 QA-Lab2 Japanese university entrance exams English translation development and test dataset. As a result, our system achieved 90% accuracy with imbalanced datasets machine learning model for the NTCIR-12 QA-Lab2 development datasets.
關鍵字Answer Validation;Imbalanced Datasets;Machine Learning;Question Answering;QA-Lab;Support Vector Machine
語言英文(美國)
收錄於
會議性質國際
校內研討會地點
研討會時間20160728~20160730
通訊作者
國別美國
公開徵稿
出版型式
出處Proceedings of the 2016 IEEE 17th International Conference on Information Reuse and Integration (IEEE IRI 2016)
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