Boosting and Rocchio applied to text filtering
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Support Vector Data Description
Machine Learning
CyberIR --- A Technological Approach to Fight Cybercrime
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Robust query-specific pseudo feedback document selection for query expansion
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Toward supervised anomaly detection
Journal of Artificial Intelligence Research
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We applied active learning techniques based on Support Vector Machine for evaluating documents each iteration, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. However, the initial retrieved documents, which are displayed to a user, sometimes don't include relevant documents. In order to solve this problem, we propose a new feedback method using information of non-relevant documents only. We named this method non-relevance feedback document retrieval. The non-relevance feedback document retrievals are based on One Class Support Vector Machine and Support Vector Data Description. Our experimental results show that One Class Support Vector Machine based method can retrieve relevant documents efficiently using information of non-relevant documents only.