Research Summaries

Back Data Mining Methods Emphasizing Mining Data Sets Gathered Via the Common Crawl

Fiscal Year 2015
Division Graduate School of Engineering & Applied Science
Department Electrical & Computer Engineering
Investigator(s) Kragh, Frank E.
Sponsor Laboratory for Telecommunications Sciences (Other-Fed)
Summary Data mining is the computational process of discovering patterns in large data sets involving methods from artificial intelligence, machine learning, random processes, and information technology. The overall goal of the data mining process is to extract patterns and knowledge from a large amount of data, thereby enabling useful predictions. It involves data access, data pre-processing, model and inference considerations, metrics, complexity considerations, and visualization.
The objective of this work is to explore, develop, and test data mining tools and techniques applicable to large data sets such as those gathered by Common Crawl.
Keywords
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal