TAILIEUCHUNG - Báo cáo khoa học: "Entity Type Variation across Two Biomedical Subdomains"

There are lexical, syntactic, semantic and discourse variations amongst the languages used in various biomedical subdomains. It is important to recognise such differences and understand that biomedical tools that work well on some subdomains may not work as well on others. We report here on the semantic variations that occur in the sublanguages of two biomedical subdomains, . cell biology and pharmacology, at the level of named entity information. By building a classifier using ratios of named entities as features, we show that named entity information can discriminate between documents from each subdomain. . | What s in a Name Entity Type Variation across Two Biomedical Subdomains Claudiu Mihăilă and Riza Theresa Batista-Navarro National Centre for Text Mining School of Computer Science University of Manchester Manchester Interdisciplinary Biocentre 131 Princess Street M1 7DN Manchester UK Abstract There are lexical syntactic semantic and discourse variations amongst the languages used in various biomedical subdomains. It is important to recognise such differences and understand that biomedical tools that work well on some subdomains may not work as well on others. We report here on the semantic variations that occur in the sublanguages of two biomedical subdomains . cell biology and pharmacology at the level of named entity information. By building a classifier using ratios of named entities as features we show that named entity information can discriminate between documents from each subdomain. More specifically our classifier can distinguish between documents belonging to each subdomain with an accuracy of F-score. 1 Introduction Biomedical information extraction efforts in the past decade have focussed on fundamental tasks needed to create intelligent systems capable of improving search engine results and easing the work of biologists. More specifically researchers have concentrated mainly on named entity recognition mapping them to concepts in curated databases Krallinger et al. 2008 and extracting simple binary relations between entities. Recently an increasing number of resources that facilitate the training of systems to extract more detailed information have become available . PennBioIE Kulick et al. 2004 GENETAG Tanabe et al. 2005 BioInfer Pyysalo et al. 2007 GENIA Kim et al. 2008 GREC Thompson et al. 2009 and Metaknowledge GE-NIA Thompson et al. 2011 . Moreover several other annotated corpora have been developed for shared task purposes such as BioCreative I II III Arighi et al. 2011 and

• Báo cáo khoa học
• Entity Type Variation
• Two Biomedical Subdomains
• Workshops
• 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
• 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