Information Elasticity Concepts Applied to Information Overload and Language Processing
Abstract
The PI, Dr. Ram Narayanan, is focused on machine learning and data analytics for numerous sensors (like with radar or cyber data collection) that leverage information elasticity concepts addressing information overload and “language� processing. In information elasticity Ram explores various data techniques to expose information, such that the information (derived from data) is elastic providing multiple perspectives of the information. A concern here is information overload, which is information-data causing a flood of data overwhelming the working space in which humans and machine then fail to be effective. Also, Ram’s interest is leveraging “language� processing to filter the information-data so as to control working with the use of information-data. In decision making processes, the effectiveness of decisions changes as amount of available information changes. Information in a general sense includes data, signals, or processes which increase the knowledge level of a decision maker. There is an optimum value of information quantity that maximized decision effectiveness. Some of the major challenges to be investigated in this context include- develop metrics to assess data quality and data reliability, quantify the effects of age of information, fill in missing data, recognize redundant data, and the use of a “language� (symbols-words) that specify control in the use-collection of information-data thereby minimizing errors and overload.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 29, 2024
- Source ID
- FA95502310294
Entities
People
- Ram M Narayanan
Organizations
- Air Force Office of Scientific Research
- Pennsylvania State University
- United States Air Force