Frequent-Itemset Mining Using Locality-Sensitive Hashing

  • Debajyoti BeraEmail author
  • Rameshwar Pratap
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9797)


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.


Hash Function Frequent Itemsets Jaccard Similarity Time Overhead Apriori Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Indraprastha Institute of Information Technology-Delhi (IIIT-D)New DelhiIndia
  2. 2.TCS Innovation LabsNew DelhiIndia

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