Mapping Data Between Probability Spaces in Probabilistic Databases

Abstract

Representation and modeling of probabilistic data is one of the areas that needs attention. In this paper, we summarize our previous work on how probabilistic data can be represented along three different probability spaces, namely, attribute probability space, record probability space, and database state probability space. Then we introduce techniques for mapping the data from the attribute probability space to record probability space and from record probability space to database state probability space. The ability to perform correct mappings of data between these probability spaces is important in order to preserve the integrity of the data and avoid any data loss during the mapping process.

Towards A Broader Adoption of Agile Software Development Methods

“…Software systems research and development has resulted in many applications covering various aspects of our lives [1][2][3][4][5]. Over the years, two major approaches for managing the software development process have evolved.…”