A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
The nature of statistical learning theory
The nature of statistical learning theory
Boosting and Rocchio applied to text filtering
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Interactive document retrieval with relational learning
Proceedings of the 2001 ACM symposium on Applied computing
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Relevance Feedback using Support Vector Machines
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Neural Computation
Active mining project: overview
AM'03 Proceedings of the Second international conference on Active Mining
A few steps towards on-the-fly symbol recognition with relevance feedback
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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We investigate the following data mining problems from the document retrieval: From a large data set of documents, we need to find documents that relate to human interest as few iterations of human testing or checking as possible. In each iteration a comparatively small batch of documents is evaluated for relating to the human interest. We apply active learning techniques based on Support Vector Machine for evaluating successive batches, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. In this paper, we adopt several representations of the Vector Space Model and several selecting rules of displayed documents at each iteration, and then show the comparison results of the effectiveness for the document retrieval in these several situations.