International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Predicate-Based RDF Indexing Using Hadoop MapReduce for Storage Optimization and Efficient Semantic Data Retrieval |
|---|---|
| ABSTRACT | Resource Description Framework (RDF) is widely used for Semantic Web applications and graph-based data management [1][10]. Traditional RDF storage generates redundancy due to repeated predicate representation, increasing storage requirements and affecting retrieval performance. This paper proposes a Predicate-Based RDF Indexing approach using Hadoop MapReduce to optimize RDF storage and improve retrieval efficiency [2][3]. The movie dataset was transformed into RDF format and processed using Hadoop Streaming with Python-based mapper and reducer implementations. Experimental results demonstrate a reduction in RDF storage from 7.09 MB to 5.02 MB, achieving approximately 29.26% storage optimization while maintaining accessibility and scalability. |
| AUTHOR | PINTUKUMARI BERA, DR. BRIJ BIHARI DUBEY, DR. ASHUTOSH ABHANGIC Research Scholar, ITMVU, Baroda, India Research Guide, ITMVU, Baroda, India Mentor, ITMSLS, Baroda, India |
| VOLUME | 186 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1407049 |
| pdf/49_Predicate-Based RDF Indexing Using Hadoop MapReduce for Storage Optimization and Efficient Semantic Data Retrieval.pdf | |
| KEYWORDS | |
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