e-commerce website without review using hui algorithm
Poornachander Karunagaran ,Vignesh Ravikumar,A.Thiyagarajan
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:4 Issue:3 Year: 01 April,2016 Pages:839-844
Abstract
Mining high utility item sets (HUIs) from databases is an important data mining task, which refers to the discovery of item sets with high utilities (e.g. high profits). However, it may present too many HUIs to users, which also degrades the efficiency of the mining process. To achieve high efficiency for the mining task and provide a concise mining result to users, we propose a novel framework in this paper for mining closed high utility item sets (CHUIs), which serves as a compact and lossless representation of HUIs. We propose three efficient algorithms named AprioriCH (Apriori-based algorithm for mining High utility Closed þ item sets), AprioriHC-D (AprioriHC algorithm with Discarding unpromising and isolated items) and CHUD (Closed þ High Utility Item set Discovery) to find this representation. Further, a method called DAHU (Derive All High Utility Item sets) is proposed to recover all HUIs from the set of CHUIs without accessing the original database. Results on real and synthetic datasets show that the proposed algorithms are very efficient and that our approaches achieve a massive reduction in the number of HUIs. In addition, when all HUIs can be recovered by DAHU, the combination of CHUD and DAHU outperforms the state-of-the-art algorithms for mining HUIs
Kewords
Frequent item set, closed high utility item set, lossless and concise representation, utility mining, and data mining
Reference
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