Novel Metaknowledge-Based Processing Technique for Multimediata Big Data Clustering Challenges
Year: 2015
Type: conference-paper
Abstract: Past research has challenged us with the task of showing relational patterns between text-based data and then clustering for predictive analysis using Golay Code technique. We focus on a novel approach to extract metaknowledge in multimedia datasets. Our collaboration has been an on-going task of studying the relational patterns between data points based on met features extracted from metaknowledge in multimedia datasets. Those selected are significant to suit the mining technique we applied, Golay Code algorithm. In this research paper we summarize findings in optimization of metaknowledge representation for 23-bit representation of structured and unstructured multimedia data in order to be processed in 23-bit Golay Code for cluster recognition.
Authors: Nima Bari, Roman Vichr, Kamran Kowsari, Simon Y. Berkovich
Institution: George Washington University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1509924779