Automatic trend detection: Time-biased document clustering (open access)

Automatic trend detection: Time-biased document clustering

This article presents a novel approach of introducing a weighted temporal feature to bias a topic clustering toward articles in a similar time frame, performed over a set of finance journal abstracts from 1974 to 2020 to demonstrate how time can be emphasized in trend detection. The authors detect trending finance topics that are not identifiable when we use a standard clustering approach with no temporal bias.
Date: March 2, 2021
Creator: Behpour, Sahar; Mohammadi, Mohammadmahdi; Albert, Mark; Alam, Zinat S.; Wang, Lingling & Xiao, Ting
System: The UNT Digital Library
Design and Assessment of a Task-Driven Introductory Data Science Course Taught Concurrently in Multiple Languages: Python, R, and MATLAB (open access)

Design and Assessment of a Task-Driven Introductory Data Science Course Taught Concurrently in Multiple Languages: Python, R, and MATLAB

This article is from the 26th ACM Conference on Innovation and Technology in Computer Science Education and discusses the design, effectiveness, and curricular impacts of an introductory data science course focused on practical programming skills and allowing students to concurrently complete the course in Python, R, or MATLAB. Students indicated a preference for the multi-language course design and the course became the recommended first programming course for a newly developed and approved undergraduate data science majors.
Date: June 26, 2021
Creator: Xiao, Ting; Greenberg, Ronald I. & Albert, Mark
System: The UNT Digital Library
Unsupervised learning in images and audio to produce neural receptive fields: a primer and accessible notebook (open access)

Unsupervised learning in images and audio to produce neural receptive fields: a primer and accessible notebook

This article presents a consolidated review of Independent Component Analysis (ICA) as an efficient neural coding scheme with the ability to model early visual and auditory neural processing.
Date: October 19, 2021
Creator: Urs, Namratha; Behpour, Sahar; Georgaras, Angie & Albert, Mark
System: The UNT Digital Library