You may recall that last fall LOCI began working with graduate students enrolled in George Mason University’s Master’s program in Data Analytics Engineering capstone class DAEN 690 to conduct research on the bleeding edge of analytics and AI. After a rigorous semester and projects that were directed by both GMU faculty and LOCI Developers, we are please to report that the project outcomes were quite productive.
Students in the capstone course were divided into two separate teams that worked on different research projects. They received direction and weekly mentoring throughout their research.
The first project was referred to as AMoD, short for Autonomous Merging of Datasets. Though details of this research cannot be disclosed, overall, the work was successful. A lot of research was conducted which yielded a lot of data collection. Though the semester is over, the majority of this student group has elected to continue working on the project with our fearless developer we’ve since deemed ‘Professor’ Mike Aebig (the only student not continuing has graduated!). Currently, the group is working on preparing an abstract for the paper they will be submitting to a scientific journal and conference presentation with a target of August 2019.
Concurrent project number 2 posed the essential question of what correlation exists between public mentions of a certain technology and prevalence of related patents. In order to understand such data trends, the students observed and conducted what is known as ‘sentiment analysis.’ This type of analysis uses Natural Language Processing (NLP) to understand an opinion expressed about a specific topic over time. The output of this analysis is known as a ‘polarity score,’ which can be produced through analyzing single sentences, paragraphs, or entire news articles. The majority of the data sets in this research actually didn’t work so well, aside from one with the application of Topic Modeling with a coherence measure, which should not be considered a failure; the team is learning what can and should be considered and changed for further research on these trends. This project will also be an ongoing component for students in the capstone course.
It’s no doubt that the research LOCI is overseeing with students of GMU’s Data Analytics capstone course is fascinating. And of course, as part of any rigorous curriculum, there is a lot of reflection on the results and refinement moving forward for the next students to carry forward the torch. LOCI looks forward to continuing this ambitious endeavor as it begins a new spring semester with our partners at GMU.
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