TAILIEUCHUNG - Báo cáo khoa học: "Text Summarization Evaluation"

The T I P S T E R Text Summarization Evaluation (SUMMAC) has established definitively that automatic text summarization is very effective in relevance assessment tasks. Summaries as short as 17% of full text length sped up decisionmaking by almost a factor of 2 with no statistically significant degradation in Fscore accuracy. SUMMAC has also introduced a new intrinsic method for automated evaluation of informative summaries. | Proceedings of EACL 99 The TIPSTER SƯMMAC Text Summarization Evaluation Inderjeet Mani David House Gary Klein Lynette Hirschman The MITRE Corporation 11493 Sunset Hills Rd. Reston VA 22090 USA Therese Firmin Department of Defense 9800 Savage Rd. Ft. Meade MD 20755 USA Beth Sundheim SPAWAR Systems Center Code D44208 53140 Gatchell Rd. San Diego CA 92152 USA Abstract The TIPSTER Text Summarization Evaluation SUMMAC has established definitively that automatic text summarization is very effective in relevance assessment tasks. Summaries as short as 17 of full text length sped up decisionmaking by almost a factor of 2 with no statistically significant degradation in F-score accuracy. SUMMAC has also introduced a new intrinsic method for automated evaluation of informative summaries. 1 Introduction In May 1998 the . government completed the TIPSTER Text Summarization Evaluation SUMMAC which was the first large-scale developer-independent evaluation of automatic text summarization systems. The goals of the SUMMAC evaluation were to judge individual summarization systems in terms of their usefulness in specific summarization tasks and to gain a better understanding of the issues involved in building and evaluating such systems. Text Summarization Text summarization is the process of distilling the most important information from a set of sources to produce an abridged version for particular users and tasks Maybury 1995 . Since abridgment is crucial an important parameter to summarization is the level of compression ratio of summary length to source length desired. Summaries can be used to indicate what topics are addressed in the source text and thus can be used to alert the user as to source content the indicative function . In addition summaries can also be used to stand in place of the source the informative function . 202 Burlington Rd. Bedford MA 01730 They can even offer a critique of the source the evaluative function Sparck-Jones 1998 . Often summaries are .

• Báo cáo khoa học
• Text Summarization Evaluation
• Lynette Hirschman
• Long Papers
• scientific reports
• model language
• process natural language
• A Framework for the Evaluation of Text
• Summarization Systems
• Enrique Amig
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Using Leading Text
• News Summaries
• Evaluation Results and Implications
• Commercial Summarization Applications
• 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
• 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