arXiv Open Access 2016

Frequent-Itemset Mining using Locality-Sensitive Hashing

Debajyoti Bera Rameshwar Pratap

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Abstrak

The Apriori algorithm is a classical algorithm for the frequent itemset mining problem. A significant bottleneck in Apriori is the number of I/O operation involved, and the number of candidates it generates. We investigate the role of LSH techniques to overcome these problems, without adding much computational overhead. We propose randomized variations of Apriori that are based on asymmetric LSH defined over Hamming distance and Jaccard similarity.

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Penulis (2)

Debajyoti Bera

Rameshwar Pratap

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Bera, D., Pratap, R. (2016). Frequent-Itemset Mining using Locality-Sensitive Hashing. https://arxiv.org/abs/1603.01682

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Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓