TAILIEUCHUNG - Báo cáo khoa học: "Multilingual Harvesting of Cross-Cultural Stereotypes"

People rarely articulate explicitly what a native speaker of a language is already assumed to know. So to acquire the stereotypical knowledge that underpins much of what is said in a given culture, one must look to what is implied by language rather than what is overtly stated. Similes are a convenient vehicle for this kind of knowledge, insofar as they mark out the most salient aspects of the most frequently evoked concepts. | Multilingual Harvesting of Cross-Cultural Stereotypes Tony Veale School of Computer Science University College Dublin Belfield Dublin 4 Ireland Yanfen Hao School of Computer Science University College Dublin Belfield Dublin 4 Ireland Guofu Li School of Computer Science University College Dublin Belfield Dublin 4 Ireland Abstract People rarely articulate explicitly what a native speaker of a language is already assumed to know. So to acquire the stereotypical knowledge that underpins much of what is said in a given culture one must look to what is implied by language rather than what is overtly stated. Similes are a convenient vehicle for this kind of knowledge insofar as they mark out the most salient aspects of the most frequently evoked concepts. In this paper we perform a multilingual exploration of the space of common-place similes by mining a large body of Chinese similes from the web and comparing these to the English similes harvested by Veale and Hao 2007 . We demonstrate that while the simile-frame is inherently leaky in both languages a multilingual analysis allows us to filter much of the noise that otherwise hinders the knowledge extraction process. In doing so we can also identify a core set of stereotypical descriptions that exist in both languages and accurately map these descriptions onto a multilingual lexical ontology like HowNet. Finally we demonstrate that conceptual descriptions that are derived from common-place similes are extremely compact and predictive of ontological structure. 1 Introduction Direct perception of our environment is just one of the ways we can acquire knowledge of the world. Another more distinctly human approach is through the comprehension of linguistic descriptions of another person s perceptions and beliefs. Since computers have limited means of human-like perception the latter approach is also very much suited to the automatic acquisition of world knowledge by a

• Báo cáo khoa học
• Multilingual Harvesting
• Cross Cultural Stereotypes
• Tony Veale
• 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