Web Science and Digital Libraries Research Group

I'm very excited to announce our recent publication at the prestigious "ACM Computing Surveys" journal. Vijini Mallawaarachchi, Lakmal Meegahapola, Roshan Madhushanka, Eranga Heshan, Dulani Meedeniya, and Sampath Jayarathna. "Change Detection and Notification of Web Pages: A Survey." ACM Computing Surveys (CSUR) 53, no. 1 (2020): 1-35 ArXiv copy is available at  https://arxiv.org/abs/1901.02660 We present our work on various aspects of change detection and notification systems, and different techniques used for each aspect including current challenges and areas of improvement within the field of research.  This project was initially a part of the early work at the Texas A&M University Center for the study of Digital Libraries (CSDL) group , on building a topic modeling based change detection classifier for ACM Conference proceedings. These initial results were presented at ACM Hypertext 2016, and IEEE Big Data Special Session on Data Mining 2016.

Today, I went to the 2020 ODU Undergraduate Research Symposium (URS). This year, the symposium is held in the Learning Commons, P erry Library , running from 8 am to 12:30 am, including both poster and oral sessions. According to the key organizer Eddie Hill , there are 45 posters. The total number of exhibitions is 125, including posters, oral, and art exhibits. I sat in two oral sessions and went through almost all posters. There are several works that drew my attention, especially the ones that apply machine learning (ML) and neural networks (NN) on cross-disciplinary research. I briefly describe them below. 1. Radio Frequency Signal Classification and detection of Drones based on Machine Learning     by Michael Nilsen , mentored by Dr. Sachin Shetty , Electrical and Computer Engineering     The goal of the research is to develop a classifier to distinguish between UAS (unmanned aircraft system) signals and non-UAS signals in multiple bands. For a particular band (e.g., 5