Speeding-Up Association Rule Mining With Inverted Index Compression

IEEE Transactions on Cybernetics
Jose Maria LunaSebastian Ventura

Abstract

The growing interest in data storage has made the data size to be exponentially increased, hampering the process of knowledge discovery from these large volumes of high-dimensional and heterogeneous data. In recent years, many efficient algorithms for mining data associations have been proposed, facing up time and main memory requirements. Nevertheless, this mining process could still become hard when the number of items and records is extremely high. In this paper, the goal is not to propose new efficient algorithms but a new data structure that could be used by a variety of existing algorithms without modifying its original schema. Thus, our aim is to speed up the association rule mining process regardless the algorithm used to this end, enabling the performance of efficient implementations to be enhanced. The structure simplifies, reorganizes, and speeds up the data access by sorting data by means of a shuffling strategy based on the hamming distance, which achieve similar values to be closer, and considering both an inverted index mapping and a run length encoding compression. In the experimental study, we explore the bounds of the algorithms' performance by using a wide number of data sets that comprise either thousands or...Continue Reading

References

Oct 21, 2006·The Journal of Infectious Diseases·Timothy L Cover
Jun 15, 2013·Nature·Vivien Marx
Aug 20, 2014·IEEE Transactions on Cybernetics·Sen ZhangJason T L Wang
Sep 30, 2014·IEEE Transactions on Cybernetics·Deng Cai, Xinlei Chen
Nov 6, 2014·IEEE Transactions on Cybernetics·Slim BechikhLamjed Ben Said
Nov 22, 2014·IEEE Transactions on Cybernetics·José María LunaSebastián Ventura
Nov 22, 2014·IEEE Transactions on Cybernetics·Gao HuangCheng Wu
Nov 25, 2014·IEEE Transactions on Cybernetics·Xianglong LiuXuelong Li
Jan 7, 2015·IEEE Transactions on Cybernetics·Yinfu FengXuelong Li

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Citations

Sep 30, 2017·IEEE Transactions on Cybernetics·Jose Maria LunaSebastian Ventura
Nov 18, 2019·PeerJ. Computer Science·Hesam HasanpourKeivan Navi

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