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Document classification with hierarchically structured dictionaries

Publication Type : Journal Article

Publisher : Advances in Intelligent Systems and Computing, Springer Verlag

Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 385, p.387-397 (2016)

Url :

ISBN : 9783319232577

Keywords : Dictionary learning, Distributed environments, Document Classification, Emerging topics, Hierarchical dictionary structure, Information retrieval systems, Innovative algorithms, Intelligent systems, Structured dictionary, Worker nodes

Campus : Amritapuri

School : School of Engineering, Department of Computer Science and Engineering

Department : Computer Science

Year : 2016

Abstract : Classification, clustering of documents, detecting novel documents, detecting emerging topics etc in a fast and efficient way, is of high relevance these days with the volume of online generated documents increasing rapidly. Experiments have resulted in innovative algorithms, methods and frameworks to address these problems. One such method is Dictionary Learning. We introduce a new 2-level hierarchical dictionary structure for classification such that the dictionary at the higher level is utilized to classify the K classes of documents. The results show around an 85% recall during the classification phase. This model can be extended to distributed environment where the higher level dictionary should be maintained at the master node and the lower level ones should be kept at worker nodes. © Springer International Publishing Switzerland 2016.

Cite this Research Publication : Remya Rajesh and Aswathi, P., “Document classification with hierarchically structured dictionaries”, Advances in Intelligent Systems and Computing, vol. 385, pp. 387-397, 2016

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