In this talk I will go back to basics with ontologies and from that project forwards to their future. I'll base most of what I talk about on my experience in bio-ontologies, but most experience will be applicable in many domains; most domains are not as special as they think. When it comes down to the basics, we need to know what our data represent or mean; that is where ontologies come into play; We need to know what we're talking about. Once we have that clear we can proceed. There is much that one can do with data once we know what it means. We can exploit those data through knowing what it represents. We can exploit these data better if our ontologies are also better. In taking this simple point of view forwards, I will use this talk to establish a set of principles for ontologists.
Department of Decision and Information Sciences
School of Business Administration,
Rochester, MI 48309
The Web is becoming an important source of event information and repository due to its real-time, open, and dynamic features. In this research, web resources based states detecting algorithm of an event is developed in order to let the people know of an emergency event and help social groups and first responders handle these events effectively. The relationship between the Web and emergency events is first introduced, which is the foundation of using Web resources to detect the state of emergency events imaged on the web. Second, five temporal features of emergency events are developed to provide the basis for state detection. Moreover, the outbreak power and the fluctuation power are presented to integrate the above temporal features for measuring the different states of an emergency event. Using these two powers, an automatic state detecting algorithm for emergency events is proposed. In addition, heuristic rules for detecting the states of emergency event on the Web are discussed. Our evaluations using real-world data sets demonstrate the utility of the proposed algorithm, in terms of performance and effectiveness in the analysis of emergency events.
Vijayan Sugumaran is Professor of Management Information Systems and Chair of the Department of Decision and Information Sciences at Oakland University, Rochester, Michigan, USA. He is also the Co-Director for the Center for Data Science and Big Data Analytics. He received his Ph.D in Information Technology from George Mason University, Fairfax, Virginia, USA. His research interests are in the areas of Big Data Analytics, Intelligent Information Technologies, Ontologies and Semantic Web. He has published over 200 peer-reviewed articles and edited twelve books. He has published in top-tier journals such as Information Systems Research, ACM Transactions on Database Systems, IEEE Transactions on Engineering Management, Communications of the ACM, IEEE Transactions on Education, IEEE Software, IEEE Transactions on Big Data, and European Journal of Information Systems. Dr. Sugumaran is the editor-in-chief of the International Journal of Intelligent Information Technologies. He also serves on the editorial board of eight journals. He is the Chair of the Intelligent Agent & Multi-Agent Systems mini-track for Americas Conference on Information Systems (AMCIS 1999 - 2019). He has served as the program co-chair for the 14th Annual Workshop on E-Business (2015) and the International Conference on Applications of Natural Language to Information Systems (NLDB 2008, 2013, 2016 and 2019). He serves as program committee member for numerous national and international conferences.