# A Survey of Utility-Oriented Pattern Mining

arXiv: https://arxiv.org/abs/1805.10511 · HTML: https://mlsanity.com/paper/1805.10511/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 May 2018.

## Built on by (most cited first, 27 of 27)

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- [US-Rule: Discovering Utility-driven Sequential Rules](https://mlsanity.com/paper/2111.15020/) (2021)
- [Anomaly Rule Detection in Sequence Data](https://mlsanity.com/paper/2111.15026/) (2021)
- [TargetUM: Targeted High-Utility Itemset Querying](https://mlsanity.com/paper/2111.00309/) (2021)
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- [Graph Contrastive Learning on Multi-label Classification for Recommendations](https://mlsanity.com/paper/2501.06985/) (2025)
- [Flexible Pattern Discovery and Analysis](https://mlsanity.com/paper/2111.12218/) (2021)
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- [Towards Revenue Maximization with Popular and Profitable Products](https://mlsanity.com/paper/2202.13041/) (2022)
- [Smart System: Joint Utility and Frequency for Pattern Classification](https://mlsanity.com/paper/2206.04269/) (2022)
- [Towards Target High-Utility Itemsets](https://mlsanity.com/paper/2206.06157/) (2022)
- [Itemset Utility Maximization with Correlation Measure](https://mlsanity.com/paper/2208.12551/) (2022)
- [A Generic Algorithm for Top-K On-Shelf Utility Mining](https://mlsanity.com/paper/2208.14230/) (2022)
- [Towards Correlated Sequential Rules](https://mlsanity.com/paper/2210.15637/) (2022)
- [Towards Sequence Utility Maximization under Utility Occupancy Measure](https://mlsanity.com/paper/2212.10452/) (2022)
- [HUSP-SP: Faster Utility Mining on Sequence Data](https://mlsanity.com/paper/2212.14255/) (2022)
- [Extended High Utility Pattern Mining: An Answer Set Programming Based Framework and Applications](https://mlsanity.com/paper/2303.13191/) (2023)
- [Discovering Utility-driven Interval Rules](https://mlsanity.com/paper/2309.16102/) (2023)
- [Mining Frequent Structures in Conceptual Models](https://mlsanity.com/paper/2406.07129/) (2024)
- [Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification](https://mlsanity.com/paper/2604.25968/) (2026)

## Abstract (arXiv)

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 and constraints have been proposed, such as support, confidence, sequence order, and utility parameters (e.g., weight, price, profit, quantity, satisfaction, etc.). In recent years, there has been an increasing demand for utility-oriented pattern mining (UPM, or called utility mining). 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 in detail, 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.