Abstract
Graph is a way of representing data as a web of relationships. Graphs consist of nodes and edges where nodes are concepts and edges are the relationships. Graph analytics is the science of solving problems expressed on graphs. Graph analytics is useful for finding hidden patterns, relationships, similarities and anomalies in graphs. These tasks are useful in many application areas like protein analysis, fraud detection, health care, computer security, financial data analysis, etc. Minimum description length (MDL) comes from information theory, which can be used for universal coding or universal modeling. SUBstructure Discovery Using Examples (SUBDUE) algorithm uses MDL to discover substructures. In this paper, the use of MDL for graph analytics is shown by applying MDL encoding to various graph datasets and in particular graph matching is solved using MDL. Further, comparative analysis is done to show how MDL value changes w.r.t. varying graph properties. subgen tool is used to generate graph datasets. Statistical tests are applied and we came to know in which cases MDL value changes significantly.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
