Results 41 to 50 of about 2,164 (156)
Mining actionable combined patterns satisfied both utility and frequency criteria [PDF]
University of Technology Sydney. Faculty of Engineering and Information Technology.In recent years, the importance of identifying actionable patterns has become increasingly recognized so that decision-support actions can be inspired by the resultant ...
Shao, Jingyu
core
Maximizing Welfare in Social Networks under a Utility Driven Influence Diffusion Model
Motivated by applications such as viral marketing, the problem of influence maximization (IM) has been extensively studied in the literature. The goal is to select a small number of users to adopt an item such that it results in a large cascade of ...
Abramowitz B. +6 more
core +1 more source
Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups
ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei +2 more
wiley +1 more source
Improved Genetic Algorithm for High-Utility Itemset Mining
High-utility itemset mining (HUIM) is an important research topic in the data mining field. Typically, traditional HUIM algorithms must handle the exponential problem of huge search space when the database size or number of distinct items is very large ...
Qiang Zhang +3 more
doaj +1 more source
Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them
This review presents a new taxonomy to summarize one‐class classification (OCC) algorithms and their applications. The main argument is that OCC should not learn multiple classes. The paper highlights common violations of OCC involving multiple classes.
Toshitaka Hayashi +3 more
wiley +1 more source
EHAUPM: Efficient High Average-Utility Pattern Mining With Tighter Upper Bounds
High-utility itemset mining (HUIM) has become a popular data mining task, as it can reveal patterns that have a high-utility, contrarily to frequent pattern mining, which focuses on discovering frequent patterns.
Jerry Chun-Wei Lin +3 more
doaj +1 more source
Efficient Analysis of Pattern and Association Rule Mining Approaches
The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules.
Lazzez, Amor, Slimani, Thabet
core +1 more source
Efficient Utility Tree-Based Algorithm to Mine High Utility Patterns Having Strong Correlation
High Utility Itemset Mining (HUIM) is one of the most investigated tasks of data mining. It has broad applications in domains such as product recommendation, market basket analysis, e-learning, text mining, bioinformatics, and web click stream analysis ...
Rashad Saeed +3 more
doaj +1 more source
We build a new, open‐source global copper deposit dataset (GCDD), facilitating AI‐driven data analysis for exploration targeting and improving our understanding of copper mineralizing systems and their mappable expressions. The GCDD hosts information about 1483 copper deposits worldwide, capturing key deposit attributes such as location, genetic type ...
Bin Wang +2 more
wiley +1 more source
High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers the utilities for businesses of items (such as profits and margins) that are discovered from transactional databases.
Cao Tùng Anh +2 more
doaj +1 more source

