Automatic condensation of electronic publications by sentence selection
Information Processing and Management: an International Journal - Special issue: summarizing text
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
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Multi-paragraph segmentation of expository text
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
The use of unlabeled data to improve supervised learning for text summarization
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A critique and improvement of an evaluation metric for text segmentation
Computational Linguistics
Title Generation Using a Training Corpus
CICLing '01 Proceedings of the Second International Conference on Computational Linguistics and Intelligent Text Processing
Text Summarization as Controlled Search
AI '02 Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Multidocument summarization: An added value to clustering in interactive retrieval
ACM Transactions on Information Systems (TOIS)
Headline generation based on statistical translation
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
A Gradual Combination of Features for Building Automatic Summarisation Systems
TSD '09 Proceedings of the 12th International Conference on Text, Speech and Dialogue
Title generation for machine-translated documents
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Todas as palavras da sentença como métrica para um sumarizador automático
Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
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Human-quality text summarization systems are difficult to design, and even more difficult to evaluate, in part because documents can differ along several dimensions, such as length, writing style and lexical usage. Nevertheless, certain cues can often help suggest the selection of sentences for inclusion in a summary. This paper presents an analysis of news-article summaries generated by sentence extraction. Sentences are ranked for potential inclusion in the summary using a weighted combination of linguistic features - derived from an analysis of news-wire summaries. This paper evaluates the relative effectiveness of these features. In order to do so, we discuss the construction of a large corpus of extraction-based summaries, and characterize the underlying degree of difficulty of summarization at different compression levels on articles in this corpus. Results on our feature set are presented after normalization by this degree of difficulty.