PPLSA: Parallel Probabilistic Latent Semantic Analysis Based on MapReduce - Intelligent Information Processing VI
Conference Papers Year : 2012

PPLSA: Parallel Probabilistic Latent Semantic Analysis Based on MapReduce

Abstract

PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalability of computation in PLSA. In this paper, we propose a parallel PLSA algorithm called PPLSA to accommodate large corpus collections in the MapReduce framework. Our solution efficiently distributes computation and is relatively simple to implement.
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hal-01524958 , version 1 (19-05-2017)

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Ning Li, Fuzhen Zhuang, Qing He, Zhongzhi Shi. PPLSA: Parallel Probabilistic Latent Semantic Analysis Based on MapReduce. 7th International Conference on Intelligent Information Processing (IIP), Oct 2012, Guilin, China. pp.40-49, ⟨10.1007/978-3-642-32891-6_8⟩. ⟨hal-01524958⟩
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