Accurate user directed summarization from existing tools
Proceedings of the seventh international conference on Information and knowledge management
Advantages of query biased summaries in information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A system for query-specific document summarization
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
User-model based personalized summarization
Information Processing and Management: an International Journal
Automatic Personalized Summarization Using Non-negative Matrix Factorization and Relevance Measure
IWSCA '08 Proceedings of the 2008 IEEE International Workshop on Semantic Computing and Applications
Query based summarization using non-negative matrix factorization
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Automatic query-based personalized summarization that uses pseudo relevance feedback with NMF
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
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With the fast growth of the Internet access by user, it has increased the necessity of the personalized summarization method. This paper proposes automatic personalized text summarization agent using generic relevance weight based on non-negative matrix factorization (NMF). The proposed agent uses generic relevance weight to summarize generic summary so that it can extract sentences covering the major and sub topics of the search results with respect to user interesting. Besides, it can improve the quality of summarization since extracting sentences to reflect the inherent semantics of the search results by using the weighted NMF. The experimental results demonstrate that the proposed method achieves better performance the other methods.