TAILIEUCHUNG - Báo cáo khoa học: "Robust Generic and Query-based Summarisation"

We present a robust summarisation system developed within the GATE architecture that makes use of robust components for semantic tagging and coreference resolution provided by GATE. Our system combines GATE components with well established statistical techniques developed for the purpose of text summarisation research. The system supports "generic" and query-based summarisation addressing the need for user adaptation. Here, we present a summarisation system that makes use of robust components for semantic tagging and coreference resolution provided by GATE (Cunningham et al., 2002). . | Robust Generic and Query-based Summarisation Horacio Saggion Kalina Bontcheva Hamish Cunningham Department of Computer Science University of Sheffield 211 Portobello Street - Sheffield - SI 4DP England - United Kingdom saggion kalina hamish @ Abstract We present a robust summarisation system developed within the GATE architecture that makes use of robust components for semantic tagging and coreference resolution provided by GATE. Our system combines GATE components with well established statistical techniques developed for the purpose of text summarisation research. The system supports generic and query-based summarisation addressing the need for user adaptation. 1 Introduction Two approaches are generally considered in automatic text summarisation research the shallow sentence extraction approach and the deep understand and generate approach Mani 2000 . Sentence extraction methods are quite robust but sentence extracts suffer from lack of cohesion and coherence. Methods that identify the essential information of the document by either information extraction or text understanding and that use the key information to produce a new text lead to high-quality summarisation Paice and Jones 1993 Saggion and Lapalme 2002 but suffer from the knowledge-bottleneck problem adapting information extraction rules templates and generation grammars to new tasks or domains is time consuming. An alternative to these approaches is to use combination of robust techniques for semantic tagging together with statistical methods Saggion 2002 . Here we present a summarisation system that makes use of robust components for semantic tagging and coreference resolution provided by GATE Cunningham et al. 2002 . Our system combines GATE components with well established statistical techniques developed for the purpose of text summarisation. The result is the sentence extraction system shown in Figure 1 the relevant sentences of the document are highlighted in the GATE user interface.

• Báo cáo khoa học
• Robust Generic
• Query based Summarisation
• Horacio Saggion Kalina Bontcheva Hamish
• 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