Information Extraction from Ontology using Distributed Environment

Abstract

Today we live in era of information. Every kind of information is easily available. It is because of Internet. Digitization of data help us to store very large amount of information. To store these large amount of data, we use system like database and server. From last two decades the data growth increases rapidly. Today every day and every moment, data is increasing on Internet. Conventional database system like SQL is quit inefficient for this type of data growth. To overcome this problem, we need other type of data storage system. Semantic Web comes into picture here. Semantic web uses an ontology to store data. Ontology is type of graph database. Ontology uses RDF, which shows the relationship between web resources. Web resources are presented in the form of URI. SPARQL is query language to extract the information from Ontology. Semantic Web gives facility of single store database like Apache Jena but it has limit of storage. Query processing is also challenge. Due to these reasons distributed environment comes into picture. RDF data can be converted to N-Triple format. This N-Triple data-set can be loaded to Apache Hive. Hive runs on top of the Hadoop. After loading this N-Triple format, Hive query is executed. Hive internally convert query in to map-reduce and gives the results. We have executed different queries on Apache Hive and Apache Jena. We found that Apache Hive performs better than Apache Jena.