Research on MapReduce-Based Rocchio Relevance Feedback in Massive Information Filtering

Wen Chuan Yang; Zhi Dong Shang; Zhi Cheng Zhang

doi:10.4028/www.scientific.net/AMR.962-965.2712

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 962-965Research on MapReduce-Based Rocchio Relevance...

Research on MapReduce-Based Rocchio Relevance Feedback in Massive Information Filtering

Abstract:

Traditional text classification algorithms have vital impact on information filtering. However, their performances were confined to a large extent in terms of the massive data set. This paper proposes an approach using MapReduce-based Rocchio relevance feedback algorithm, which improved the traditional Rocchio algorithm in the MapReduce paradigm, to resolve the problem of massive information filtering. The experiments on Hadoop cluster showed an effective improvement in performance by using the new method.

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Periodical:

Advanced Materials Research (Volumes 962-965)

Pages:

2712-2715

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.962-965.2712

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Online since:

June 2014

Authors:

Wen Chuan Yang, Zhi Dong Shang, Zhi Cheng Zhang

Keywords:

Filtering, MapReduce, Rocchio, Text Classification

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