TAILIEUCHUNG - Báo cáo khoa học: "Reading Level Assessment Using Support Vector Machines and Statistical Language Models"

Reading proficiency is a fundamental component of language competency. However, finding topical texts at an appropriate reading level for foreign and second language learners is a challenge for teachers. This task can be addressed with natural language processing technology to assess reading level. Existing measures of reading level are not well suited to this task, but previous work and our own pilot experiments have shown the benefit of using statistical language models. In this paper, we also use support vector machines to combine features from traditional reading level measures, statistical language models, and other language processing tools to produce. | Reading Level Assessment Using Support Vector Machines and Statistical Language Models Sarah E. Schwarm Dept. of Computer Science and Engineering University of Washington Seattle Wa 98195-2350 sarahs@ Mari Ostendorf Dept. of Electrical Engineering University of Washington Seattle Wa 98195-2500 mo@ Abstract Reading proficiency is a fundamental component of language competency. However finding topical texts at an appropriate reading level for foreign and second language learners is a challenge for teachers. This task can be addressed with natural language processing technology to assess reading level. Existing measures of reading level are not well suited to this task but previous work and our own pilot experiments have shown the benefit of using statistical language models. In this paper we also use support vector machines to combine features from traditional reading level measures statistical language models and other language processing tools to produce a better method of assessing reading level. 1 Introduction The . educational system is faced with the challenging task of educating growing numbers of students for whom English is a second language . Dept. of Education 2003 . In the 2001-2002 school year Washington state had 72 215 students of all students in state programs for Limited English Proficient LEP students Bylsma et al. 2003 . In the same year one quarter of all public school students in California and one in seven students in Texas were classified as LEP . Dept. of Education 2004 . Reading is a critical part of language and educational development but finding appropriate reading material for LEP students is often diffi cult. To meet the needs of their students bilingual education instructors seek out high interest level texts at low reading levels . texts at a first or second grade reading level that support the fifth grade science curriculum. Teachers need to find material at a variety of levels since .

• Báo cáo khoa học
• Reading Level Assessment
• Support Vector Machines
• Statistical Language Models
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Integrated format
• Reading assessment
• Reading performance
• Split attention
• Pre proficiency level
• 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