This chapter provides an introduction to high utility itemset mining, reviews the state-of-the-art algorithms, their extensions, applications, and discusses research opportunities. This chapter is aimed both at those who are new to the field of high utility itemset mining, as well as researchers...
The term utility refers to the importance or the usefulness of the appearance of the itemset in transactions quantified in terms like profit , sales or any other user preferences. In High Utility Itemset Mining the objective is to identify itemsets that have utility values above a given utility...
A survey of incremental high-utility itemset mining 作者:Gan, Wensheng; Lin, Jerry Chun-Wei*; Fournier-Viger, Philippe; Chao, Han-Chieh; Hong, Tzung-Pei; Fujita, Hamido 来源:Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery , 2018, 8(2): e1242. DOI:10.1002/widm.1242 ...
Frequent Item set Mining (FIM) treats all items having the same importance or same profit and it assumes that every item in a transaction in the same level and it is very difficult to find the High utility item (HUI) without redundancy. FIM cannot satisfy the requirement of users who ...
Knowledge mining is a widely active research area across disciplines such as natural language processing (NLP), data mining (DM), and machine learning (ML). The overall objective of extracting knowledge from data source is to create a structured representation that allows researchers to better under...
B Rász,F Bodon,L Schmidt - 《Osdm Proceedings of International Workshop on Open Source Data Mining Frequent Pattern》 被引量: 30发表: 2005年 A Survey on High Utility Itemset Mining from Transactional Databases Data Mining can be defined as an activity that extracts some new nontrivial infor...
The problem of high-utility itemset mining (HUIM) has specifically garnered huge research attention, as it aims to find relevant information on patterns in a database, which conform to a user-defined utility function. The mined patterns are used for making data-backed decisions in the fields...
FHM (Fournier-Viger et al., ISMIS 2014) is an algorithm for discovering high-utility itemsets in a transaction database containing utility information. FHMFreq is a simple extension of FHM for discovering frequent high-utility itemsets (it combines frequent itemset mining with high-utility item...
Incremental high average-utility itemset mining: survey and challenges Article Open access 30 April 2024 Cities can benefit from complex supply chains Article Open access 29 March 2023 Introduction Optimal operation of a supply chain (SC) remains a challenging task. A major obstacle to efficient...
High utility itemset miningInfrequent itemset miningRare itemset miningItemset mining is a popular extension to the frequent pattern mining problem in data mining. Finding infrequent patterns, however, has gained its importance due to proven utility in the areas of web mining, bioinformatics and ...