Los Angeles

Research Article Open Access

Analysis of Top-K Utility Pattern Mining Framework


S.S. Naghate, S.S. Sherekar, V.M. Thakare


P.G. Dept. of Computer Science and Engineering, Sant Gadge Baba Amravati University, Amravati,
Maharashtra 444602, India

Adv. Mater. Proc., 2020, 5 (3), 20030404

DOI: 10.5185/amp.2020.030404

Publication Date (Web):04/07/2020

Copyright © IAAM-VBRI Press


A new algorithm of utility-list structure has been proposed in this paper which based on the framework of top-k utility mining analysed. There are many techniques which extracts top keyword within search space relates with various algorithms. Like, High Utility Pattern Mining, which is detection of high utility itemsets in a transactional database; provides the fundamental task in database and data mining community, such as quantity, cost, weight and profits concern, to extract remarkable knowledge and efficient database patterns. Different from the support based mining models; the utility oriented mining framework integrates the utility theory to provide more informative and useful patterns. These could not be directly performed on the utility mining techniques with the help of proposed method in this paper would find a top-k search space itemsets. This paper is focused on analysis of many identical high top-k utility patterns mining algorithm, such as mining for Top-K High Utility Itemsets, Solutions to Utility Big Data Analysis, Negative Sequential Patterns Mining, Efficient High Pattern Mining with Tighter Upper Bounds and Tighter Upper Bound including Average-Utility for Mining High Average-Utility Patterns. However there are some issues that need to resolve. These are discussed in this paper and efficient proposed the analysis of the various utility 


Top-k High utility patterns, TKUL-miner, sequential patterns, frequent itemset mining, knowledge discovery database.