TAILIEUCHUNG - Báo cáo khoa học: "Automatic Discovery of Intentions in Text and its Application to Question Answering"

Semantic relations between text concepts denote the core elements of lexical semantics. This paper presents a model for the automatic detection of INTENTION semantic relation. Our approach first identifies the syntactic patterns that encode intentions, then we select syntactic and semantic features for a SVM learning classifier. In conclusion, we discuss the application of INTENTION relations to Q&A. | Automatic Discovery of Intentions in Text and its Application to Question Answering Marta Tatu Human Language Technology Research Institute Department of Computer Science University of Texas at Dallas Richardson TX 75080 USA marta@ Abstract Semantic relations between text concepts denote the core elements of lexical semantics. This paper presents a model for the automatic detection of INTENTION semantic relation. Our approach first identifies the syntactic patterns that encode intentions then we select syntactic and semantic features for a SVM learning classifier. In conclusion we discuss the application of INTENTION relations to Q A. 1 Introduction Problem description Intentions comprise of semantic relationships that express a human s goal-oriented private states of mind including intents objectives aims and purposes. As a relation it encodes information that might not be explicitly stated in text and its detection might require inferences and human judgment. The answer to the question What was Putin trying to achieve by increasing military cooperation with North Korea is found in the sentence Putin is attempting to restore Russia s influence in the East Asian region. Extracting the exact answer to restore Russia s influence in the East Asian region becomes easier if this is recognized as Putin s intention which matches the question s expected answer. In this paper we describe a method that identifies intentions in domain independent texts. We employed two machine learning algorithms to create models that locate intentions in a given paragraph using a set of six syntactic and semantic features. Motivation The current state-of-the-art NLP systems cannot extract intentions from open text and as we saw in the example their detection benefits Question Answering. An intention is the answer to general questions like What is the goal ofX What does Xplan to do or What does X aim for The INTENTION semantic relation is one of the most challenging .

• Báo cáo khoa học
• Automatic Discovery of Intentions in Text
• Application to Question Answering
• Marta Tatu
• 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