Searching for Maximal Holes in Databases
Document Type
Oral Presentation
Campus where you would like to present
SURC 137B
Start Date
21-5-2015
End Date
21-5-2015
Keywords
Maximal Empty Rectangle, Maximal Cuboid, Big Data
Abstract
The problem of finding maximal empty rectangles in a set of points in 2D and 3D space has been well studied, and efficient algorithms exist to identify maximal rectangles in 2D space. Unfortunately, such efficiency is lacking in higher dimensions where the problem has been shown to be NP complete when the dimensions are included in the input. We compare existing methods and suggest a novel technique to discover interesting maximal empty hyper-rectangles in cases where dimensionality and input size would otherwise make analysis impractical. Applications include big data analysis, recommender systems, automatic knowledge discovery, and query optimization.
Recommended Citation
Lemley, Joseph, "Searching for Maximal Holes in Databases" (2015). Symposium Of University Research and Creative Expression (SOURCE). 8.
https://digitalcommons.cwu.edu/source/2015/oralpresentations/8
Department/Program
Computer Science
Additional Mentoring Department
Computer Science
Searching for Maximal Holes in Databases
SURC 137B
The problem of finding maximal empty rectangles in a set of points in 2D and 3D space has been well studied, and efficient algorithms exist to identify maximal rectangles in 2D space. Unfortunately, such efficiency is lacking in higher dimensions where the problem has been shown to be NP complete when the dimensions are included in the input. We compare existing methods and suggest a novel technique to discover interesting maximal empty hyper-rectangles in cases where dimensionality and input size would otherwise make analysis impractical. Applications include big data analysis, recommender systems, automatic knowledge discovery, and query optimization.
Faculty Mentor(s)
Razvan Andonie