Web Science
Research in Web Science is broad and covers many aspects of the Web from its algorithmic models and search to individual and social use. Models of the web focus on rich graphs and networks and their content and evolution.
Research involves unique information and knowledge extraction and the construction of academic digital libraries such as CiteSeerX for computer and information science and ChemXSeer for chemistry. User analysis aims to extract patterns and discover knowledge from large-scale Web activity data to better understand information retrieval behaviors of users, and to better predict the interactions among people through cyber-enabled social networks, online gaming, and virtual environments on the Web. Through these understandings, the goals and activities of virtual communities can be better supported.
Research topics include mining temporal patterns from large-scale data, graphical representation of knowledge, information extraction and retrieval, machine learning, image search, and using the Web for large-scale experimental social science studies.
Research involves unique information and knowledge extraction and the construction of academic digital libraries such as CiteSeerX for computer and information science and ChemXSeer for chemistry. User analysis aims to extract patterns and discover knowledge from large-scale Web activity data to better understand information retrieval behaviors of users, and to better predict the interactions among people through cyber-enabled social networks, online gaming, and virtual environments on the Web. Through these understandings, the goals and activities of virtual communities can be better supported.
Research topics include mining temporal patterns from large-scale data, graphical representation of knowledge, information extraction and retrieval, machine learning, image search, and using the Web for large-scale experimental social science studies.
