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Frequent pattern mining: current status and future directions
Frequent pattern mining has been a focused theme in data mining research for over a
decade. Abundant literature has been dedicated to this research and tremendous progress …
decade. Abundant literature has been dedicated to this research and tremendous progress …
Graph mining: Laws, generators, and algorithms
How does the Web look? How could we tell an abnormal social network from a normal one?
These and similar questions are important in many fields where the data can intuitively be …
These and similar questions are important in many fields where the data can intuitively be …
Improving graph neural network expressivity via subgraph isomorphism counting
While Graph Neural Networks (GNNs) have achieved remarkable results in a variety of
applications, recent studies exposed important shortcomings in their ability to capture the …
applications, recent studies exposed important shortcomings in their ability to capture the …
[ספר][B] Data mining: the textbook
CC Aggarwal - 2015 - Springer
This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …
complex data types and their applications, capturing the wide diversity of problem domains …
Graph based anomaly detection and description: a survey
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …
such as security, finance, health care, and law enforcement. While numerous techniques …
Fast rule mining in ontological knowledge bases with AMIE
Recent advances in information extraction have led to huge knowledge bases (KBs), which
capture knowledge in a machine-readable format. Inductive logic programming (ILP) can be …
capture knowledge in a machine-readable format. Inductive logic programming (ILP) can be …
Frequent pattern mining algorithms: A survey
This chapter will provide a detailed survey of frequent pattern mining algorithms. A wide
variety of algorithms will be covered starting from Apriori. Many algorithms such as Eclat …
variety of algorithms will be covered starting from Apriori. Many algorithms such as Eclat …
Dgcnn: A convolutional neural network over large-scale labeled graphs
Exploiting graph-structured data has many real applications in domains including natural
language semantics, programming language processing, and malware analysis. A variety of …
language semantics, programming language processing, and malware analysis. A variety of …
AMIE: association rule mining under incomplete evidence in ontological knowledge bases
Recent advances in information extraction have led to huge knowledge bases (KBs), which
capture knowledge in a machine-readable format. Inductive Logic Programming (ILP) can …
capture knowledge in a machine-readable format. Inductive Logic Programming (ILP) can …
Experimental security analysis of a modern automobile
Modern automobiles are no longer mere mechanical devices; they are pervasively
monitored and controlled by dozens of digital computers coordinated via internal vehicular …
monitored and controlled by dozens of digital computers coordinated via internal vehicular …