Novel Metaknowledge-based Processing Technique for Multimedia Big Data clustering challenges
Databases
2018-10-24 v1 Artificial Intelligence
Information Retrieval
Multimedia
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 datapoints based on metafeatures 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
Cite
@article{arxiv.1503.00245,
title = {Novel Metaknowledge-based Processing Technique for Multimedia Big Data clustering challenges},
author = {Nima Bari and Roman Vichr and Kamran Kowsari and Simon Y. Berkovich},
journal= {arXiv preprint arXiv:1503.00245},
year = {2018}
}
Comments
IEEE Multimedia Big Data (BigMM 2015)