TAILIEUCHUNG - Báo cáo khoa học: "Experiments with Interactive Question-Answering"

This paper describes a novel framework for interactive question-answering (Q/A) based on predictive questioning. Generated off-line from topic representations of complex scenarios, predictive questions represent requests for information that capture the most salient (and diverse) aspects of a topic. We present experimental results from large user studies (featuring a fully-implemented interactive Q/A system named F ERRET) that demonstrates that surprising performance is achieved by integrating predictive questions into the context of a Q/A dialogue. . | Experiments with Interactive Question-Answering Sanda Harabagiu Andrew Hickl John Lehmann and Dan Moldovan Language Computer Corporation Richardson Texas USA sanda@ Abstract This paper describes a novel framework for interactive question-answering Q A based on predictive questioning. Generated off-line from topic representations of complex scenarios predictive questions represent requests for information that capture the most salient and diverse aspects of a topic. We present experimental results from large user studies featuring a fully-implemented interactive Q A system named Ferret that demonstrates that surprising performance is achieved by integrating predictive questions into the context of a Q A dialogue. 1 Introduction In this paper we propose a new architecture for interactive question-answering based on predictive questioning. We present experimental results from a currently-implemented interactive Q A system named Ferret that demonstrates that surprising performance is achieved by integrating sources of topic information into the context of a Q A dialogue. In interactive Q A professional users engage in extended dialogues with automatic Q A systems in order to obtain information relevant to a complex scenario. Unlike Q A in isolation where the performance of a system is evaluated in terms of how well answers returned by a system meet the specific information requirements of a single question the performance of interactive Q A systems have traditionally been evaluated by analyzing aspects of the dialogue as a whole. Q A dialogues have been evaluated in terms of 1 efficiency defined as the number of questions that the user must pose to find particular information 2 effectiveness defined by the relevance of the answers returned 3 user satisfaction. In order to maximize performance in these three areas interactive Q A systems need a predictive dialogue architecture that enables them to propose related questions about the relevant .

• Báo cáo khoa học
• Experiments with Interactive Question Answering
• Sanda Harabagiu
• Andrew Hickl
• John Lehmann
• and Dan Moldovan
• 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