Main Reference PaperFuzzy Web Data Tables Integration Guided by an Ontological and Terminological Resource, IEEE Transactions on Knowledge and Data Engineering, APRIL 2013.
  • This project describes about the ONtology based Data INtEgration (ONDINE) framework used for processing web data tables. UsingOTR web data tables are integrated with fuzzy annotations. Fuzzy annotations provide approximate results according to the preferences described as fuzzy sets. Fuzzy annotated data tables are extracted using SPARQL queries.

+ Description
  • This project describes about the ONtology based Data INtEgration (ONDINE) framework used for processing web data tables. UsingOTR web data tables are integrated with fuzzy annotations. Fuzzy annotations provide approximate results according to the preferences described as fuzzy sets. Fuzzy annotated data tables are extracted using SPARQL queries.

  • The main goal of the project is to provide the simultaneous annotation of data table with OTR. The annotations of data table are incorporated with fuzzy sets. The processing of RDF annotations is accomplished through SPARQL query and selection criteria are used to retrieve the semantically close results.

+ Aim & Objectives
  • The main goal of the project is to provide the simultaneous annotation of data table with OTR. The annotations of data table are incorporated with fuzzy sets. The processing of RDF annotations is accomplished through SPARQL query and selection criteria are used to retrieve the semantically close results.

  • The ONDINE system can be combined with Rule Based Modeling known as Hybrid methodology framework. The Rule based modeling uses additional rules to extend the modeling capabilities. Combining fuzzy annotations with rule based modeling provides an accurate result sets while querying the RDF/XML document.

+ Contribution
  • The ONDINE system can be combined with Rule Based Modeling known as Hybrid methodology framework. The Rule based modeling uses additional rules to extend the modeling capabilities. Combining fuzzy annotations with rule based modeling provides an accurate result sets while querying the RDF/XML document.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, GlassFish 4.1.1, J2EE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, GlassFish 4.1.1, J2EE.

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.