Teaching Learning Based Optimization in Semantic Web of Distributed RDF
Kura Shailaja1, Puligadda Veereswara Kumar2, Sarvadevabhatla Durga Bhavani3 

1Kura Shailaja, Department of Computer Science and Engineering, Methodist College of Engineering and Technology, Hyderabad, India.
2Puligadda Veereswara Kumar, Department of Computer Science and Engineering, Osmania University, Hyderabad, India.
3Sarvadevabhatla Durga Bhavani, Department of Computer Science and Engineering, Jawaharlal Nehru Technological University Hyderabad, Hyderabad, India.

Manuscript received on 08 March 2019 | Revised Manuscript received on 16 March 2019 | Manuscript published on 30 July 2019 | PP: 5381-5389 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3191078219/19©BEIESP | DOI: 10.35940/ijrte.B3191.078219

Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Semantic web data use as a unified data model in various areas, such as Bioinformatics, media data, Wikipedia, social networks, and government open data. Sharing information among people using semantic web helps to understand and manipulation of information. In the semantic web, the Resource Description Framework (RDF) denotes the linked data. The logical data is represented as RDF model to manage the unformatted data and it provides an ability to machine interpretability of data. The major problem on the web is to handle the large volume of the data that also has other challenges like query processing and optimization over widely distributed RDF data. In this research, the Teacher Learning based Optimization (TLBO) algorithm is proposed for the query optimization to reduce query cost, and optimize the computation time of the query. The TLBO technique select the suitable location and size of the population based on the data that effectively provide the solution for the distributed data i.e.., triple pattern of semantic web. The experimental result showed that the TLBO in query optimization performed well in the manner of query computation time compared to existing methods like MARVEL. Additionally, the results showed that the proposed TLBO model achieved nearly 4.93 seconds for executing the multiple queries in LUBM dataset.
Index Terms: Resource Description Framework, Structural Query Language, Semantic Web, Teaching Learning Based Optimization, Query Optimizer.

Scope of the Article: Design Optimization of Structures