TAILIEUCHUNG - Báo cáo khoa học: "Fertility Models for Statistical Natural Language Understanding"

Several recent efforts in statistical natural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; Levin and Pieraccini, 1995; Epstein et al., 1996; Epstein, 1996). This paper extends the IBM Machine Translation Group's concept of fertility (Brown et al., 1993) to the generation of clumps for natural language understanding. The basic underlying intuition is that a single concept may be expressed in English as many disjoint clump of words. . | Fertility Models for Statistical Natural Language Understanding Stephen Della Pietra Mark Epstein Salim Roukos Todd Ward IBM Thomas J. Watson Research Center . Box 218 Yorktown Heights NY 10598 USA Now With Renaissance Technologies Stonybrook NY USA meps roukos tward Abstract Several recent efforts in statistical natural language understanding NLU have focused on generating clumps of English words from semantic meaning concepts Miller et al. 1995 Levin and Pierac-cini 1995 Epstein et al. 1996 Epstein 1996 . This paper extends the IBM Machine Translation Group s concept of fertility Brown et al. 1993 to the generation of clumps for natural language understanding. The basic underlying intuition is that a single concept may be expressed in English as many disjoint clump of words. We present two fertility models which attempt to capture this phenomenon. The first is a Poisson model which leads to appealing computational simplicity. The second is a general nonparametric fertility model. The general model s parameters are bootstrapped from the Poisson model and updated by the EM algorithm. These fertility models can be used to impose clump fertility structure on top of preexisting clump generation models. Here we present results for adding fertility structure to unigram bigram and headword clump generation models on ARPA s Air Travel Information Service ATỈS domain. 1 Introduction The goal of a natural language understanding NLU system is to interpret a user s request and respond with an appropriate action. We view this interpretation as translation from a natural language expression E into an equivalent expression F in an unambigous formal language. Typically this formal language will be hand-crafted to enhance performance on some task-specific domain. A statistical NLƯ system translates a request E as the most likely formal expression F according to a probability model p F arg maxp F E arg maxp F E . over all F over all F We have .

• Báo cáo khoa học
• Fertility Models
• Statistical Natural Language Understanding
• Workshops
• scientific reports
• model language
• process natural language
• Khejri based cropping models
• Soil fertility
• Scope of improvement
• Hot arid environment
• Cluster bean and vegetables
• Molecular Basis
• Diagnosis and Staging
• Fertility and Fecundity
• Chemotherapy for Childhood
• Childhood Cancer
• Fatigue in Pediatric
• Mesh Stent
• Malignant Portal
• Vein Stenosis
• BMC Genomics
• Heat stress
• Genotype by environment interaction
• Reaction norm
• Single step GWAS
• Biological informed models
• Kernel based prediction
• Sire conception rate
• Genomic prediction
• 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
• 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