TAILIEUCHUNG - Báo cáo khoa học: "Finding Word Substitutions Using a Distributional Similarity Baseline and Immediate Context Overlap"

This paper deals with the task of finding generally applicable substitutions for a given input term. We show that the output of a distributional similarity system baseline can be filtered to obtain terms that are not simply similar but frequently substitutable. Our filter relies on the fact that when two terms are in a common entailment relation, it should be possible to substitute one for the other in their most frequent surface contexts. Using the Google 5-gram corpus to find such characteristic contexts, we show that for the given task, our filter improves the precision of a distributional similarity. | Finding Word Substitutions Using a Distributional Similarity Baseline and Immediate Context Overlap Aurelie Herbelot University of Cambridge Computer Laboratory . Thompson Avenue Cambridge ah433@ Abstract This paper deals with the task of finding generally applicable substitutions for a given input term. We show that the output of a distributional similarity system baseline can be filtered to obtain terms that are not simply similar but frequently substitutable. Our filter relies on the fact that when two terms are in a common entailment relation it should be possible to substitute one for the other in their most frequent surface contexts. Using the Google 5-gram corpus to find such characteristic contexts we show that for the given task our filter improves the precision of a distributional similarity system from 41 to 56 on a test set comprising common transitive verbs. 1 Introduction This paper looks at the task of finding word substitutions for simple statements in the context of KB querying. Let us assume that we have a knowledge base made of statements of the type subject - verb - object 1. Bank of America - acquire - Merrill Lynch 2. Lloyd s-buy-HBOS 3. Iceland - nationalise - Kaupthing Let us also assume a simple querying facility where the user can enter a word and be presented with all statements containing that word in a typical search engine fashion. If we want to return all acquisition events present in the knowledge base above as opposed to nationalisation events we might search for acquire . This will return the first statement about the acquisition of Merrill Lynch but not the second statement about HBOS. Ideally we would like a system able to generate words similar to our query so that a statement containing the verb buy gets returned when we search for acquire . This problem is closely related to the clustering of semantically similar terms which has received much attention in the literature. Systems that perform such clustering usually

• Báo cáo khoa học
• Finding Word Substitutions
• a Distributional Similarity Baseline
• Immediate Context Overlap
• 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
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• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln