Efficient vertical mining of high utility quantitative itemsets

Li, Chia Hua; Wu, Cheng; Tseng, Vincent S.

doi:10.1109/grc.2014.6982826

Cited by 9 publications

(19 citation statements)

References 22 publications

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“…In the framework of HUQI mining, an item may have different quantities in the database and each item carrying a different quantity is regarded as a quantitative item. HUQI [39] and more efficient vertical utility-list-based VHUQI [119] were thus developed. An example of such a rule is (bread, 3, 4) ⇒ (milk, 2, 3), which means that most customers who purchased three or four breads also purchased two or three milks.…”

Section: Mining High-utility Quantitative Itemsets/rulesmentioning

confidence: 99%

“…However, such information can be very useful and valuable in many applications. In view of this, the concept of High-Utility Quantitative Itemset mining (abbreviated as HUQI) [39], [119] has emerged. In the framework of HUQI mining, an item may have different quantities in the database and each item carrying a different quantity is regarded as a quantitative item.…”

Section: Mining High-utility Quantitative Itemsets/rulesmentioning

confidence: 99%

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A Survey of Utility-Oriented Pattern Mining

Gan

Lin

Fournier‐Viger

et al. 2021

IEEE Trans. Knowl. Data Eng.

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240

148

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The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications to derive beneficial knowledge. For identifying and evaluating the usefulness of different kinds of patterns, many techniques/constraints have been proposed, such as support, confidence, sequence order, and utility parameters (e.g., weight, price, profit, quantity, etc.). In recent years, there has been an increasing demand for utility-oriented pattern mining (UPM). UPM is a vital task, with numerous high-impact applications, including cross-marketing, e-commerce, finance, medical, and biomedical applications. This survey aims to provide a general, comprehensive, and structured overview of the state-of-the-art methods of UPM. First, we introduce an in-depth understanding of UPM, including concepts, examples, and comparisons with related concepts. A taxonomy of the most common and state-of-the-art approaches for mining different kinds of high-utility patterns is presented, including Apriori-based, tree-based, projection-based, vertical-/horizontal-data-format-based, and other hybrid approaches. A comprehensive review of advanced topics of existing high-utility pattern mining techniques is offered, with a discussion of their pros and cons. Finally, we present several well-known open-source software packages for UPM. We conclude our survey with a discussion on open and practical challenges in this field.

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Section: Mining High-utility Quantitative Itemsets/rulesmentioning

confidence: 99%

Section: Mining High-utility Quantitative Itemsets/rulesmentioning

confidence: 99%

A Survey of Utility-Oriented Pattern Mining

Gan

Lin

Fournier‐Viger

et al. 2021

IEEE Trans. Knowl. Data Eng.

Self Cite

240

148

View full text Add to dashboard Cite

show abstract

“…Motivated by the success of utility-list based algorithms, a vertical based algorithm (VHUQI) for HUQIM was proposed [19]. It utilizes a variation of the utility-list structure.…”

Section: Related Workmentioning

confidence: 99%

“…To address this limitation, High Utility Quantitative Itemset Mining (HUQIM) was proposed as an extension of HUIM. The objective of HUQIM is to discover all sets of items that have a high utility while also providing information about item quantities that led to this utility [18,19,30,33]. The additional information about item quantities can be very useful as illustrated by the following example.…”

Section: Introductionmentioning

confidence: 99%