PCA-Based Relevance Feedback in Document Image Retrieval
Research has been devoted in the past few years to relevance
feedback as an effective solution to improve performance of
information retrieval systems. Relevance feedback refers to an
interactive process that helps to improve the retrieval
performance. In this paper we propose the use of relevance
feedback to improve document image retrieval System (DIRS)
performance. This paper compares a variety of strategies for
positive and negative feedback. In addition, feature subspace is
extracted and updated during the feedback process using a
Principal Component Analysis (PCA) technique and based on
users feedback. That is, in addition to reducing the
dimensionality of feature spaces, a proper subspace for each type
of features is obtained in the feedback process to further improve
the retrieval accuracy. Experiments show that using relevance
Feedback in DIR achieves better performance than common DIR.
Keywords: Relevance Feedback; Document Image; Information Retrieval; Principal Component Analysis.
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ABOUT THE AUTHORS
Reza Tavoli
Faculty of Department of Mathematics, Islamic Azad University, Chalous Branch (IAUC),17 Shahrivar Ave., P.O. Box 46615-397, Chalous, Iran
Fariborz Mahmoudi
Faculty Of Department of Computer and electrical Qazvin Islamic Azad University Qazvin, Iran
Reza Tavoli
Faculty of Department of Mathematics, Islamic Azad University, Chalous Branch (IAUC),17 Shahrivar Ave., P.O. Box 46615-397, Chalous, Iran
Fariborz Mahmoudi
Faculty Of Department of Computer and electrical Qazvin Islamic Azad University Qazvin, Iran
