Passage-level evidence in document retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Empirical methods for artificial intelligence
Empirical methods for artificial intelligence
Advantages of query biased summaries in information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
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
Information seeking and mediated searching. Part 4: cognitive styles in information seeking
Journal of the American Society for Information Science and Technology
Using and Evaluating User Directed Summaries to Improve Information Access
ECDL '99 Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries
User-sensitive text summarization: application to the medical domain
User-sensitive text summarization: application to the medical domain
User-model based personalized summarization
Information Processing and Management: an International Journal
Empirical evaluation of adaptive user modeling in a medical information retrieval application
UM'03 Proceedings of the 9th international conference on User modeling
Evaluation of a system for personalized summarization of web contents
UM'05 Proceedings of the 10th international conference on User Modeling
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Along with research on information retrieval and filtering, text summarization is an effective technique to help users save time in finding critical information and making timely decisions. Some existing summarization approaches have used a user’s interests to develop a personalized text summarization system. However, there is inadequate focus on exploring cognitive styles, which have been found to affect the ways users think, perceive and remember information. Our main objective of this evaluation is to investigate the effect of a user’s cognitive style on multi-document summarization. We examine two dimensions of a user’s cognitive style which are the analytic/who list and verbal/imagery dimensions. We conducted an experiment to determine the impact of a user’s cognitive style when working with different types of document sets. The type of a document set refers to whether the content of this set is loosely related or closely related. Our results show that users in general are insensitive to the types of document sets both in terms of information covered in a summary as well as the way that a summary is written and presented. However, if we group users by the analytic/who list dimension, we found that people in groups are sensitive to the way that the information is presented for different types of document sets.