INCREMENTAL ONTOLOGY INFERENCE FOR SEMANTIC WEB BASED ON MAPREDUCE APPROACH

INCREMENTAL ONTOLOGY INFERENCE FOR SEMANTIC WEB BASED ON MAPREDUCE APPROACH
Author(s):
U. Uma Devi , T.Revathi
Keywords:
Big data, Knowledge Searching, MapReduce, Ontology Inference, Semantic Web.
Abstract
In the fast growing internet world, web content increase day by day. This demands the knowledge searching and reasoning in this big data. The knowledge is represented in the semantic web using web ontology languages. Existing methods take long time to derive inferences and also it performs full reasoning when new data stream arrives. In this paper an Incremental Ontology Inference (IOI) Method for handling large number of triples (subject, predicate, and object) is proposed. In IOI, the triples for each type are collected and a forest like data structure is built and then performs reasoning. The storage requirement is also reduced by merging the triple reasoned from other triple into a set of triples with the same values. Hence, it provides fast traversal of triples in the tree and retrieves the query results efficiently. MapReduce paradigm is used to implement the proposed approach. The results for user query are reasoned and retrieved effectively.
Article Details
Unique Paper ID: 144262 Publication Volume & Issue: Volume 3, Issue 9 Page(s): 109 - 118
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org