tailieunhanh - Báo cáo khoa học: "Independence Assumptions Considered Harmful"

Many current approaches to statistical language modeling rely on independence a.~sumptions 1)etween the different explanatory variables. This results in models which are computationally simple, but which only model the main effects of the explanatory variables oil the response variable. This paper presents an argmnent in favor of a statistical approach that also models the interactions between the explanatory variables. The argument rests on empirical evidence from two series of experiments concerning automatic ambiguity resolution. . | Independence Assumptions Considered Harmful Alexander Franz Sony Computer Science Laboratory D21 Laboratory Sony Corporation 6-7-35 Kitashinagawa Shinagawa-ku Tokyo 141 Japan ami Abstract Many current approaches statistical language modeling rely on independence assumptions between the different explanatory variables. This results in models which are computationally simple but which only model the main effects of the explanatory variables on the response variable. This paper presents an argument in favor of a statistical approach that also models the interactions between the explanatory variables. The argument rests on empirical evidence from two series of experiments concerning automatic ambiguity resolution. 1 Introduction In this paper we present an empirical argument in favor of a certain approach to statistical natural language modeling we advocate statistical natural language models that account for the interactions between the explanatory statistical variables rather than relying on independence assumptions. Such models are able perform prediction on the basis of estimated probability distributions that are properly conditioned on the combinations of the individual values of the explanatory variables. After describing one type of statistical model that is particularly well-suited to modeling natural language data called a loglinear model we present empirical evidence from a series of experiments on different ambiguity resolution tasks that show that the performance of the loglinear models outranks the performance of other models described in the literature that assume independence between the explanatory variables. 2 Statistical Language Modeling By statistical language model . we refer to a mathematical object that imitates the properties of some aspects of natural language and in turn makes predictions that are useful from a scientific or engineer ing point of view. Much recent work in this framework has used written and spoken .

• Báo cáo khoa học
• Independence Assumptions
• Considered Harmful
• Alexander Franz
• scientific reports
• model language
• process natural language
• 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
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln