TAILIEUCHUNG - Báo cáo khoa học: "Chinese Term Extraction Using Different Types of Relevance"

This paper presents a new term extraction approach using relevance between term candidates calculated by a link analysis based method. Different types of relevance are used separately or jointly for term verification. The proposed approach requires no prior domain knowledge and no adaptation for new domains. | Chinese Term Extraction Using Different Types of Relevance Yuhang Yang1 Tiejun Zhao1 Qin Lu2 Dequan Zheng1 and Hao Yu1 1School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China yhyang tjzhao dqzheng yu @ Department of Computing The Hong Kong Polytechnic University Hong Kong China csluqin@ Abstract This paper presents a new term extraction approach using relevance between term candidates calculated by a link analysis based method. Different types of relevance are used separately or jointly for term verification. The proposed approach requires no prior domain knowledge and no adaptation for new domains. Consequently the method can be used in any domain corpus and it is especially useful for resource-limited domains. Evaluations conducted on two different domains for Chinese term extraction show significant improvements over existing techniques and also verify the efficiency and relative domain independent nature of the approach. 1 Introduction Terms are the lexical units to represent the most fundamental knowledge of a domain. Term extraction is an essential task in domain knowledge acquisition which can be used for lexicon update domain ontology construction etc. Term extraction involves two steps. The first step extracts candidates by unithood calculation to qualify a string as a valid term. The second step verifies them through termhood measures Kageura and Umino 1996 to validate their domain specificity. Many previous studies are conducted on term candidate extraction. Other tasks such as named entity recognition meaningful word extraction and unknown word detection use techniques similar to that for term candidate extraction. But their focuses are not on domain specificity. This study focuses on the verification of candidates by termhood calculation. Relevance between term candidates and documents is the most popular feature used for term verification such as TF-IDF Salton and McGill 1983 Frank

• Báo cáo khoa học
• Chinese Term Extraction
• Different Types of Relevance
• Yuhang Yang
• báo cáo khoa học
• báo cáo 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 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