Browsing by Author "Khan, Salman"

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    High Utility Itemset Mining Using Genetic Approach
    (Advanced Informatics for Computing Research pp 143–150, 2022) Almeida, Tracy; Khan, Salman
    Frequent Itemset Mining(FIM) aims to generate itemsets having their frequency of occurrence not lesser than minimum support specified by the user. FIM does not consider the itemset utility which is the it’s profit value. High-utility itemset mining(HUIM) mines high-utility itemsets(HUI) from data. HUIM is a combinatorial optimization. With HUIM algorithms, the time required to search increases exponentially with an increasing number of transactions and database items. To address this issue an efficient algorithm to mine HUIs is proposed. The proposed algorithm uses a compact form of chromosome encoding by eliminating the itemsets with low transactional utilities. The algorithm employs methodology of self mutation to reduce generation of unwanted chromosomes. Experimental results have shown that the proposed algorithm finds HUIs for a given threshold value. The proposed algorithm consumes less time as compared to another HUIM algorithm HUIM-IGA.
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    High-Utility Itemset Mining using Fuzzy Sets
    (Smart Innovation, Systems and Technologies (SIST,volume 326), 2023) Khan, Salman; Almeida, Tracy
    High-utility itemset mining aims to mine itemsets with high utilities. Utility of an itemset is the profit value associated with it. However, high-utility itemsets are generated considering only the occurrence of the items in the database. These patterns do not contain any information about the utilities of the items in the transaction. This paper aims to generate high-utility itemsets containing information about the utilities of the items.