A reality-rooted perspective on “explainable AI” and what this means for the future of the field.
WIREs Data Mining and Knowledge Discovery
Solving real-life problems with temporal association rules
Researchers discuss how to extract valuable information from databases to aid decision making in emergencies, such as the current pandemic.
Hey InsureBot, what do I need to buy to protect myself?
A team of data scientists has developed a general-purpose recommendation system for insurance based on Bayesian networks and deep learning.
Is Uber equally accessible everywhere?
Researchers study factors that affect the accessibility of ride-sharing programs such as Uber in Philadelphia.
Artificial astronomers
By examining a wide selection of research works from the last two years, it was very clear that astronomers are using machine learning and AI as powerful discovery tools across a range of fields.
Intersecting Machine Learning and Cybersecurity
Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty.
Crowdsourced Data to Predict Hotel Ratings
Crowdsourcing is an essential source of tourism information, especially in the accommodation sector.
Internet of Things and Data Mining
The Internet of Things is the result of the convergence of sensing, computing, and networking technologies, allowing devices of varying sizes and computational capabilities (things) to intercommunicate.
Machine Learning From Crowds: A Systematic Review Of Its Applications
Crowdsourcing opens the door to solving a wide variety of problems that previously were unfeasible in the field of machine learning, allowing us to obtain relatively low cost labeled data in a small amount of time.
There and Back Again: Outlier Detection Between Statistical Reasoning And Data Mining Algorithms
Data mining and statistics, the roots and the path of development of statistical outlier detection and of database‐related data mining methods for outlier detection.
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