Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
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Proceedings of the ninth international conference on Information and knowledge management
Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
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Fast generation of result snippets in web search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
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Introduction to Information Retrieval
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Complex objects ranking: a relational data mining approach
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Combining summaries using unsupervised rank aggregation
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
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We demonstrate ManyAspects -- a document-summarization system that ingests a document and automatically highlights a small set of sentences that are expected to cover the different aspects of the document. The sentences are picked using simple coverage and orthogonality criteria. With ManyAspects, you get a concise yet comprehensive overview of the document without having to spend lots of time drilling down into the details. The system can handle both plain text and syndication feeds (RSS and Atom). It can run either as a stand-alone application or be integrated with Web 2.0 forums to pinpoint different opinions on online discussions for blogs, products, movies, etc. For comparative analysis and exploratory flexibility, the system includes other off-the-shelf text-summarization methods, e.g. k-median clustering and singular value decomposition. Thus, the system allows the user to explore the content of the input document in many different ways.