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Process mining: software comparison, trends, and challenges
Process mining is the confluence between data mining and business process management, which is a growing and promising research topic. From process...
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Introduction to Text Mining
This chapter details the textual data, text mining operations, structure of the text information systems, and other basic concepts.
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An incremental rare association rule mining approach with a life cycle tree structure considering time-sensitive data
One of the association rule mining techniques, rare association rule mining (RARM), is a method for finding association rules with low support but...
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Frequent Pattern Mining
Frequent pattern mining deals with identifying the common trends and behaviors in datasets. These trends represent information that may not be...
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Pose pattern mining using transformer for motion classification
Capitalizing on the rapid development of diverse deep learning technologies in the field of image analysis, studies are now being conducted to detect...
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BA-flag: a self-prevention mechanism of selfish mining attacks in blockchain technology
Selfish mining is when a group of miners in a blockchain system work together to cheat and get more rewards by hiding their work from others. This...
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Mining frequent weighted utility patterns with dynamic weighted items from quantitative databases
The mining of frequent weighted utility patterns (FWUPs) is an important task in the field of data mining that aims to discover frequent patterns...
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Analyzing interconnected processes: using object-centric process mining to analyze procurement processes
The purchase-to-pay (P2P) process is one of the core business processes in any organization. It ensures the correct and efficient provisioning of...
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Mining Top-K constrained cross-level high-utility itemsets over data streams
Cross-Level High-Utility Itemsets Mining (CLHUIM) aims to discover interesting relationships between hierarchy levels by introducing the taxonomy of...
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What makes life for process mining analysts difficult? A reflection of challenges
Over the past few years, several software companies have emerged that offer process mining tools to assist enterprises in gaining insights into their...
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A bibliometric analysis of Educational Data Mining studies in global perspective
Educational Data Mining (EDM) is an interdisciplinary field that encapsulates different fields such as computer science, education, and statistics....
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Image-based random rotation for preserving the data in data mining process
The privacy and security of big data have become a major concern in recent years, necessitating privacy-preserving data mining strategies to preserve...
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Offline Mining of Microservice-Based Architectures (Extended Version)
Designing applications adhering to the key design principles of microservice-based architectures (MSAs) enables fully exploiting the potentials of...
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An effective keyword search co-occurrence multi-layer graph mining approach
A combination of tools and methods known as "graph mining" is used to evaluate real-world graphs, forecast the potential effects of a given graph’s...
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New Spark solutions for distributed frequent itemset and association rule mining algorithms
The large amount of data generated every day makes necessary the re-implementation of new methods capable of handle with massive data efficiently....
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Identifying missing data handling methods with text mining
Missing data is an inevitable aspect of every empirical research. Researchers developed several techniques to handle missing data to avoid...
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Tree-Based Unified Temporal Erasable-Itemset Mining
Erasable itemset mining is an important research area for manufacturers, as it aids in identifying less profitable materials in product datasets to...
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Parallel frequent itemsets mining using distributed graphic processing units
Data mining is an essential technique in knowledge discovery which is widely used for pattern extraction and information classification. Extracting...
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Incremental Mining on Association Rules
The discovery of association rules has been known to be useful in selective marketing, decision analysis, and business management. An important...
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A framework for proposing a liquid stock portfolio using frequent itemset mining from time-series data
Data mining provides various frequent pattern mining methods to help business owners identify items with frequency or utility values greater than a...
