The Design of kNN Text Categorization on Storm Cluster

Rui Fang Liu; Bao Jin Yu; Jiang Xue; Li Xin Xu

doi:10.4028/www.scientific.net/AMM.427-429.2701

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 427-429The Design of kNN Text Categorization on Storm...

The Design of kNN Text Categorization on Storm Cluster

Abstract:

Try to handle a big data stream for information retrieval is just a beginning from TREC KBA2012. Storm is a free and open source distributed real-time computation system, which makes it easy to reliably process unbounded streams of data. For the issue of KBA2012, the combination of k-nearest neighbor (kNN) algorithm and Storm cluster will be an effective solution. kNN classification technique stands out for its simplicity and capability of being implemented on distributed platform. In addition, the entities (categories) in the issue of KBA2012 are settled down, which corresponds to the situation in which kNN is used. The paper discussed the implementation of kNN on Storm cluster and the results of experiments with KBA2012 data set.

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Periodical:

Applied Mechanics and Materials (Volumes 427-429)

Pages:

2701-2706

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.427-429.2701

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Online since:

September 2013

Authors:

Rui Fang Liu*, Bao Jin Yu, Jiang Xue, Li Xin Xu

Keywords:

Feature Selection, KBA, KNN Classifier, Storm Cluster, Text Categorization

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* - Corresponding Author

References

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