TAILIEUCHUNG - Báo cáo khoa học: "Learning to Rank Definitions to Generate Quizzes for Interactive Information Presentation"

This paper proposes the idea of ranking definitions of a person (a set of biographical facts) to automatically generate “Who is this?” quizzes. The definitions are ordered according to how difficult they make it to name the person. Such ranking would enable users to interactively learn about a person through dialogue with a system with improved understanding and lasting motivation, which is useful for educational systems. In our approach, we train a ranker that learns from data the appropriate ranking of definitions based on features that encode the importance of keywords in a definition as well as its content | Learning to Rank Definitions to Generate Quizzes for Interactive Information Presentation Ryuichiro Higashinaka and Kohji Dohsaka and Hideki Isozaki NTT Communication Science Laboratories NTT Corporation 2-4 Hikaridai Seika-cho Kyoto 619-0237 Japan rh dohsaka isozaki @ Abstract This paper proposes the idea of ranking definitions of a person a set of biographical facts to automatically generate Who is this quizzes. The definitions are ordered according to how difficult they make it to name the person. Such ranking would enable users to interactively learn about a person through dialogue with a system with improved understanding and lasting motivation which is useful for educational systems. In our approach we train a ranker that learns from data the appropriate ranking of definitions based on features that encode the importance of keywords in a definition as well as its content. Experimental results show that our approach is significantly better in ranking definitions than baselines that use conventional information retrieval measures such as tf idf and pointwise mutual information PMI . 1 Introduction Appropriate ranking of sentences is important as noted in sentence ordering tasks Lapata 2003 in effectively delivering content. Whether the task is to convey news texts or definitions the objective is to make it easier for users to understand the content. However just conveying it in an encyclopedia-like or temporal order may not be the best solution considering that interaction between a system and a user improves understanding Sugiyama et al. 1999 and that the cognitive load in receiving information is believed to correlate with memory fixation Craik and Lockhart 1972 . In this paper we discuss the idea of ranking definitions as a way to present people s biographical information to users and propose ranking definitions to automatically generate a Who is this quiz. Here we use the term definitions of a person to mean a short series of .

• Báo cáo khoa học
• Learning to Rank Definitions
• Generate Quizzes
• Interactive Information Presentation
• 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