32 字串图形结构侦测方法 - 国立政治大学.doc

國立政治大學資訊科學系 Department of Computer Science National Chengchi University 碩士論文 Master’s Thesis 中文資訊擷取結果之錯誤偵測 Error Detection on Chinese Information Extraction Results 研 究 生：鄭雍瑋 指導教授：劉吉軒 中華民國九十五年七月 July 2006 中文資訊擷取結果之錯誤偵測 Error Detection on Chinese Information Extraction Results 研 究 生 ：鄭 雍 瑋 Student : Yung-Wei Cheng 指 導 教 授 ：劉 吉 軒 Advisors : Jyi-Shane Liu 國 立 政 治 大 學 資 訊 科 學 系 碩 士 論 文 A Thesis Submitted to Department of Computer Science National Chengchi University In partial fulfillment of the Requirements for the Degree of Master in Computer Science 中華民國 九十五 年 七 月 July 2006 中文資訊擷取結果之錯誤偵測 摘 要 資訊擷取是從自然語言文本中辨識出特定的主題或事件的描述，進而萃取出相關主題或事件元素中的對應資訊，再將其擷取之結果至資料庫中，便能將自然語言文件轉換成結構化的核心資訊。然而資訊擷取技術結果會有錯誤情況發生，若單只依靠人工檢查及更正錯誤的方式進行，將會是耗費人力及時間的工作。在本研究論文中，我們提出字串特徵值實驗結果顯示Chinese Information Extraction Results Abstract Given a targeted subject and a text collection, information extraction techniques provide the capability to populate a database in which each record entry is a subject instance documented in the text collection. However, even with the state-of-the-art IE techniques, IE task results are expected to contain errors. Manual error detection and correction are labor intensive and time consuming. This validation cost remains a major obstacle to actual deployment of practical IE applications with high validity requirement. In this paper, we propose string graph structure and string feature-based methods. The former takes advantage of graph structure to compare characters and the relation between characters. Next step, we count the corresponding score via formula, and then the scores are takes to estimate the data correctness. The latter uses string features to describe a certain characteristics of each string, after that decision tree is generated by the C4.5 and SVM machine learning algorithms. And then classify the data is valid or not. These two detection methods have the ability to describe the feature of data and verify the correctness