TAILIEUCHUNG - Báo cáo khoa học: "Japanese Dependency Structure Analysis Based on Maximum Entropy Models"

This paper describes a dependency structure analysis of Japanese sentences based on the maximum entropy models. Our model is created by learning the weights of some features from a training corpus to predict the dependency between bunsetsus or phrasal units. The dependency accuracy of our system is using the Kyoto University corpus. We discuss the contribution of each feature set and the relationship between the number of training data and the accuracy. | Proceedings of EACL 99 Japanese Dependency structure Analysis Based on Maximum Entropy Models Kiyotaka Uchimoto Satoshi Sekine Hitoshi Isahara Communications Research Laboratory Ministry of Posts and Telecommunications 588-2 Iwaoka Iwaoka-cho Nishi-ku Kobe Hyogo 651-2401 Japan uch imot oIi sahara New York University 715 Broadway 7th floor New York NY 10003 USA Abstract This paper describes a dependency structure analysis of Japanese sentences based on the maximum entropy models. Our model is created by learning the weights of some features from a training corpus to predict the dependency between bunsetsus or phrasal units. The dependency accuracy of our system is using the Kyoto University corpus. We discuss the contribution of each feature set and the relationship between the number of training data and the accuracy. 1 Introduction Dependency structure analysis is one of the basic techniques in Japanese sentence analysis. The Japanese dependency structure is usually represented by the relationship between phrasal units called bunsetsu. The analysis has two conceptual steps. In the first step a dependency matrix is prepared. Each element of the matrix represents how likely one bunsetsu is to depend on the other. In the second step an optimal set of dependencies for the entire sentence is found. In this paper we will mainly discuss the first step a model for estimating dependency likelihood. So far there have been two different approaches to estimating the dependency likelihood. One is the rule-based approach in which the rules are created by experts and likelihoods are calculated by some means including semiautomatic corpusbased methods but also by manual assignment of scores for rules. However hand-crafted rules have the following problems. They have a problem with their coverage. Because there are many features to find correct dependencies it is difficult to find them manually. They also have a problem with their consistency .

• Báo cáo khoa học
• Japanese Dependency Structure Analysis
• Maximum Entropy Models
• Kiyotaka Uchimoto
• scientific reports
• model language
• process natural language
• Detection of Quotations
• Inserted Clauses and its Application to Dependency Structure Analysis
• Spontaneous Japanese
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
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• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln