TY - GEN
T1 - A cascade multiple classifier system for document categorization
AU - Xu, Jian Wu
AU - Singh, Vartika
AU - Govindaraju, Venu
AU - Neogi, Depankar
PY - 2009
Y1 - 2009
N2 - A novel cascade multiple classifier system (MCS) for document image classification is presented in the paper. It consists of two different classifiers with different feature sets. The proceeding classifier uses image features, learns physical representation of the document, and outputs a set of candidate class labels for the second classifier. The succeeding classifier is a hierarchical classification model based on textual features. The candidate labels set from the first classifier provides subtrees for the second classifier to search in the hierarchical tree and derive a final classification decision. Hence, it reduces the computational complexity and improves classification accuracy for the second classifier. We test the proposed cascade MCS on a large scale set of tax document classification. The experimental results show improvement of classification performance over individual classifiers.
AB - A novel cascade multiple classifier system (MCS) for document image classification is presented in the paper. It consists of two different classifiers with different feature sets. The proceeding classifier uses image features, learns physical representation of the document, and outputs a set of candidate class labels for the second classifier. The succeeding classifier is a hierarchical classification model based on textual features. The candidate labels set from the first classifier provides subtrees for the second classifier to search in the hierarchical tree and derive a final classification decision. Hence, it reduces the computational complexity and improves classification accuracy for the second classifier. We test the proposed cascade MCS on a large scale set of tax document classification. The experimental results show improvement of classification performance over individual classifiers.
KW - Classifier Combination
KW - Document Classification
KW - Multiple-classifiers
UR - https://www.scopus.com/pages/publications/70349316568
U2 - 10.1007/978-3-642-02326-2_46
DO - 10.1007/978-3-642-02326-2_46
M3 - Conference contribution
AN - SCOPUS:70349316568
SN - 3642023258
SN - 9783642023255
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 458
EP - 467
BT - Multiple Classifier Systems - 8th International Workshop, MCS 2009, Proceedings
T2 - 8th International Workshop on Multiple Classifier Systems, MCS 2009
Y2 - 10 June 2009 through 12 June 2009
ER -