Automatic text structuring and summarization
Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic text summarization of scientific articles based on classification of extract's population
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Text summarisation in progress: a literature review
Artificial Intelligence Review
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Many Knowledge workers are increasingly using online resources to find out latest developments in their specialty and articles of interest. To extract relevant information from such multiple online information sources summarization is being used. Current summarization systems produce a uniform version of summary for all users. However summaries which are generic in nature do not cater to the user’s background and interests. In this paper we propose to makethe summarization process user specific and present a design for generating personalized summaries of online articles that are tailored to each person’s interest. The user’s data available on web is used for model their background and interest. A controlled user-centered qualitative evaluation carried out on news articles of science and technology domain, indicates better user satisfaction with personalized summaries compared to generic summaries.