Exponential growth has been measured in the size of data during the last two decades. The mining of utility itemsets from a large dataset is a challenging issue because of the diverse dimensions of data. Various itemset mining algorithms have been projected by the researchers to discover relations among the items of a database. In this paper, a systematic literature review has been presented for different algorithms, which are being used for utility itemset mining. 37 studies have been selected

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... to answer the research questions framed for this review based on different methods of mining. These methods have been sorted into four categories with their benefits, drawbacks, performance, and scalability. It has been concluded that research efforts should be geared towards more scalable, secure, and safe methods that can operate more meritoriously on large datasets.