Constructing literature abstracts by computer: techniques and prospects
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
The identification of important concepts in highly structured technical papers
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
New Methods in Automatic Extracting
Journal of the ACM (JACM)
Snowball: a prototype system for extracting relations from large text collections
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Using predicate-argument structures for information extraction
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Hedge Trimmer: a parse-and-trim approach to headline generation
HLT-NAACL-DUC '03 Proceedings of the HLT-NAACL 03 on Text summarization workshop - Volume 5
Combining linguistic and statistical analysis to extract relations from web documents
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Extractive summarization using inter- and intra- event relevance
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Identification of Chinese Event and Their Argument Roles
CITWORKSHOPS '08 Proceedings of the 2008 IEEE 8th International Conference on Computer and Information Technology Workshops
Labeling chinese predicates with semantic roles
Computational Linguistics
StatSnowball: a statistical approach to extracting entity relationships
Proceedings of the 18th international conference on World wide web
Extractive summarization based on event term clustering
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Investigating statistical techniques for sentence-level event classification
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
The stages of event extraction
ARTE '06 Proceedings of the Workshop on Annotating and Reasoning about Time and Events
UMSLLS '09 Proceedings of the Workshop on Unsupervised and Minimally Supervised Learning of Lexical Semantics
The automatic creation of literature abstracts
IBM Journal of Research and Development
Graph-based event coreference resolution
TextGraphs-4 Proceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing
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This paper proposes a verb-driven approach to extract 5W1H (Who, What, Whom, When, Where and How) event semantic information from Chinese online news. The main contributions of our work are two-fold: First, given the usual structure of a news story, we propose a novel algorithm to extract topic sentences by stressing the importance of news headline; Second, we extract event facts (i.e. 5W1H) from these topic sentences by applying a rule-based method (verb-driven) and a supervised machine-learning method (SVM). This method significantly improves the predicate-argument structure used in Automatic Content Extraction (ACE) Event Extraction (EE) task by considering valency (dominant capacity to noun phrases) of a Chinese verb. Extensive experiments on ACE 2005 datasets confirm its effectiveness and it also shows a very high scalability, since we only consider the topic sentences and surface text features. Based on this method, we build a prototype system named Chinese News Fact Extractor (CNFE). CNFE is evaluated on a real world corpus containing 30,000 newspaper documents. Experiment results show that CNFE can extract event facts efficiently.