ACL RD-TEC 1.0 Summarization of C04-1094
Paper Title:
USING SYNTACTIC INFORMATION TO EXTRACT RELEVANT TERMS FOR MULTI-DOCUMENT SUMMARIZATION
USING SYNTACTIC INFORMATION TO EXTRACT RELEVANT TERMS FOR MULTI-DOCUMENT SUMMARIZATION
Authors: Enrique Amigó and Julio Gonzalo and Víctor Peinado and Anselmo Peñas and Felisa Verdejo
Primarily assigned technology terms:
- automatic extraction
- automatic generation
- chunker
- clustering
- computing
- finite automata
- identification
- information access
- information extraction
- interactive summarization
- learning
- localization
- maximum likelihood
- multi-document summarization
- parser
- parsing
- shallow parser
- shallow parsing
- single-document summarization
- summarization
- summarization process
- summarization system
- summarization systems
- supervised learning
- term extraction
- topic tracking
- weighting
Other assigned terms:
- abbreviations
- adverb
- approach
- automata
- baseline measure
- candidate terms
- case
- chunk
- chunks
- compounding
- concept
- concepts
- correlation
- determiner
- distribution
- document
- document collection
- document set
- domain information
- evaluation measures
- fact
- generation
- gold standard
- likelihood
- likelihood ratio
- main verb
- measure
- measures
- mechanisms
- multi-document summarization task
- n-grams
- names
- noise
- noun compounding
- noun phrase
- noun phrases
- nouns
- np head
- phrase
- precision
- preposition
- prepositional phrases
- priori
- probabilities
- probability
- procedure
- process
- punctuation
- punctuation marks
- questionnaire
- relation
- schema
- sentence
- sentences
- sources of information
- subject noun phrase
- subordinate clauses
- summarization task
- syntactic function
- syntactic functions
- syntactic information
- syntactic position
- syntactic properties
- syntax
- term
- term list
- terms
- topics
- training
- training corpus
- user
- verb
- verb forms
- verb phrase
- vocabulary
- word
- words
