학술논문

Resource Distribution Framework Based Building and Database Management for the Artwork
Document Type
Conference
Author
Source
2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC) Mobile Networks and Wireless Communications (ICMNWC), 2023 3rd International Conference on. :1-4 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Robotics and Control Systems
Spectroscopy
Art
Digital images
Resource description framework
Software
Resource management
Painting
Artwork resources
Database building
Database Management System
Resource Distribution Framework and Painting
Language
Abstract
The utilization of Database Management System (DBMS) for artwork is a current research trend. By the help of an actual DBMS, it is capable to store, adapt, exhibit painting documents and identify documents that content particular pursuit conditions. The Resource Distribution Framework (RDF) data effective management is significant requirement for appreciating a semantic web perception. Performance as well as durability problems are attracting significantly persistent as Semantic Web technology is functional to real-time approaches. In this research, presenting the adaptable combined database compendium, which is particularly developed for painting as well as other art work obtaining as well as gratifies preservation requirement. In addition, alphanumerical data, unlimited digital images of art work of different functionalities are stored, and spectroscopy signals as well as colorimetric analysis measurements. The results show that a vertical partitioned schema obtains similar performance to property table approach though being easier to develop. The presented approach compares the performance of vertical partitioning with prior art on queries developed through Web-based RDF browser over large-scale catalog of the data.