Main Reference PaperSemantic-based and Entity-Resolution Fusion to Enhance Quality of Big RDF Data, IEEE Transactions on Big Data, 2018 [Java/Hadoop]
  • This work proposes an efficient querying approach over big RDF data. To process the big data, this work implements a four layers are such as: In first layer the RDF structure is generated by data coming from different heterogeneous sources. Next, the data are identified by URI based on the concept of ontology and then stores the RDF data into HDFS. Finally, the query the Big RDF data using MapReduce based SPARQL and query results will be retrieved.

Description
  • This work proposes an efficient querying approach over big RDF data. To process the big data, this work implements a four layers are such as: In first layer the RDF structure is generated by data coming from different heterogeneous sources. Next, the data are identified by URI based on the concept of ontology and then stores the RDF data into HDFS. Finally, the query the Big RDF data using MapReduce based SPARQL and query results will be retrieved.

  • To reduce the execution time of processing big data.

  • To reduce the response time of the queries.

Aim & Objectives
  • To reduce the execution time of processing big data.

  • To reduce the response time of the queries.

  • This work is contributed to optimize the query rewriting algorithm to minimize the number of MapReduce jobs of the query evaluation plans.

Contribution
  • This work is contributed to optimize the query rewriting algorithm to minimize the number of MapReduce jobs of the query evaluation plans.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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