TAILIEUCHUNG - Báo cáo khoa học: "A Bio-inspired Approach for Multi-Word Expression Extraction"

This paper proposes a new approach for Multi-word Expression (MWE)extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. Theory of Longest Common Subsequence (LCS) originates from computer science and has been established as affine gap model in Bioinformatics. We perform this developed LCS technique combined with linguistic criteria in MWE extraction. In comparison with traditional n-gram method, which is the major technique for MWE extraction, LCS approach is applied with great efficiency and performance guarantee. . | A Bio-inspired Approach for Multi-Word Expression Extraction Jianyong Duan Ruzhan Lu Weilin Wu Yi Hu Department of Computer Science Shanghai Jiao Tong University Shanghai 200240 . China duanjy@ lu-rz wl-wu huyi @ Yan Tian School of Foreign Languages Department of Computer Science Shanghai Jiao Tong University Shanghai 200240 . China tianyan@ cn Abstract This paper proposes a new approach for Multi-word Expression MWE extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. Theory of Longest Common Subsequence LCS originates from computer science and has been established as affine gap model in Bioinformatics. We perform this developed LCS technique combined with linguistic criteria in MWE extraction. In comparison with traditional n-gram method which is the major technique for MWE extraction LCS approach is applied with great efficiency and performance guarantee. Experimental results show that LCS-based approach achieves better results than n-gram. 1 Introduction Language is under continuous development. People enlarge vocabulary and let words carry more meanings. Meanwhile the language also develops larger lexical units to carry specific meanings specifically MWE s which include compounds phrases technical terms idioms and collocations etc. The MWE has relatively fixed pattern because every MWE denotes a whole concept. In computational view the MWE repeats itself constantly in corpus Taneli 2003 . The extraction of MWE plays an important role in several areas such as machine translation Pas-cale 1997 information extraction Kalliopi 2000 etc. On the other hand there is also a need for MWE extraction in a much more widespread scenario namely that of human translation and technical writing. Many efforts have been devoted to the study of MWE extraction Beat-rice 2003 Ivan 2002 Jordi 2001 . These statistical methods detect MWE by frequency of candidate .

• Báo cáo khoa học
• A Bio inspired Approach
• Multi Word Expression Extraction
• Jianyong Duan
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học