• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Efficient Query Retrieval from Social Data in Neo4j using LIndex

Vol. 12, No. 5, May 30, 2018
10.3837/tiis.2018.05.017, Download Paper (Free):

Abstract

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
A. B. Mathew, "Efficient Query Retrieval from Social Data in Neo4j using LIndex," KSII Transactions on Internet and Information Systems, vol. 12, no. 5, pp. 2211-2232, 2018. DOI: 10.3837/tiis.2018.05.017.

[ACM Style]
Anita Brigit Mathew. 2018. Efficient Query Retrieval from Social Data in Neo4j using LIndex. KSII Transactions on Internet and Information Systems, 12, 5, (2018), 2211-2232. DOI: 10.3837/tiis.2018.05.017.

[BibTeX Style]
@article{tiis:21764, title="Efficient Query Retrieval from Social Data in Neo4j using LIndex", author="Anita Brigit Mathew and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2018.05.017}, volume={12}, number={5}, year="2018", month={May}, pages={2211-2232}}