A trainable document summarizer
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Generating summaries of multiple news articles
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Towards multidocument summarization by reformulation: progress and prospects
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
New Methods in Automatic Extracting
Journal of the ACM (JACM)
Event tracking based on domain dependency
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Problems in automatic abstracting
Communications of the ACM
Building a Chinese-English wordnet for translingual applications
ACM Transactions on Asian Language Information Processing (TALIP)
Generating natural language summaries from multiple on-line sources
Computational Linguistics - Special issue on natural language generation
Identifying topics by position
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Sentence ordering in multidocument summarization
HLT '01 Proceedings of the first international conference on Human language technology research
From single to multi-document summarization: a prototype system and its evaluation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Multi-document summarization by sentence extraction
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
An NTU-approach to automatic sentence extraction for summary generation
TIPSTER '98 Proceedings of a workshop on held at Baltimore, Maryland: October 13-15, 1998
Clustering and visualization in a multi-lingual multi-document summarization system
ECIR'03 Proceedings of the 25th European conference on IR research
Multi-document summarization by graph search and matching
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
The impact analysis of language differences on an automatic multilingual text summarization system
Journal of the American Society for Information Science and Technology
Cross-document event clustering using knowledge mining from co-reference chains
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Multidocument Summary Generation: Using Informative and Event Words
ACM Transactions on Asian Language Information Processing (TALIP)
Storyline-based summarization for news topic retrospection
Decision Support Systems
Intelligent location-based mobile news service system with automatic news summarization
Expert Systems with Applications: An International Journal
Cross document event clustering using knowledge mining from co-reference chains
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Integrating punctuation rules and naïve bayesian model for chinese creation title recognition
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Multilingual relevant sentence detection using reference corpus
AIRS'04 Proceedings of the 2004 international conference on Asian Information Retrieval Technology
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This article proposes a summarization system for multiple documents. It employs not only named entities and other signatures to cluster news from different sources, but also employs punctuation marks, linking elements, and topic chains to identify the meaningful units (MUs). Using nouns and verbs to identify the similar MUs, focusing and browsing models are applied to represent the summarization results. To reduce information loss during summarization, informative words in a document are introduced. For the evaluation, a question answering system (QA system) is proposed to substitute the human assessors. In large-scale experiments containing 140 questions to 17,877 documents, the results show that those models using informative words outperform pure heuristic voting-only strategy by news reporters. This model can be easily further applied to summarize multilingual news from multiple sources.