Browsing by Subject "Data Science"

Now showing 1 - 2 of 2
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    Community Recommendation in Social Networks with Sparse Data
    (2020-12) Rahmaniazad, Emad; King, Brian; Jafari, Ali; Salama, Paul
    Recommender systems are widely used in many domains. In this work, the importance of a recommender system in an online learning platform is discussed. After explaining the concept of adding an intelligent agent to online education systems, some features of the Course Networking (CN) website are demonstrated. Finally, the relation between CN, the intelligent agent (Rumi), and the recommender system is presented. Along with the argument of three different approaches for building a community recommendation system. The result shows that the Neighboring Collaborative Filtering (NCF) outperforms both the transfer learning method and the Continuous bag-of-words approach. The NCF algorithm has a general format with two various implementations that can be used for other recommendations, such as course, skill, major, and book recommendations.
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    Teaching Note—Data Science in the MSW Curriculum: Innovating Training in Statistics and Research Methods
    (Taylor and Francis, 2020) Perron, Brian E.; Victor, Bryan G.; Hiltz, Barbara S.; Ryan, Joseph; School of Public and Environmental Affairs
    Recent and rapid technological advances have given rise to an explosive growth of data, along with low-cost solutions for accessing, collecting, managing, and analyzing data. Despite the advances in technology and the availability of data, social work organizations routinely encounter data-related problems that have an impact on their opportunities for making data-driven decisions. Although training in research methods and statistics is important for social work students, these courses often do not address the needs organizations face in collecting, managing, and using data for data-driven decision making. In this teaching note, we propose innovating the social work curriculum using a data science framework as a way to address the day-to-day challenges organizations face regarding data. We provide a description of data science, along with four examples of MSW student projects that were based on a data science framework.