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EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT: -

In existing system, incorrect answers the keyword search returns answers that do not correspond to real sub graphs or misses valid matches from the Underlying RDF data and inability to scale.

 They handle typical RDF datasets with tens of millions of triples.

PROPOSED SYSTEM: -

We proposed a new correct baseline solution based on the backward search technique.  This is more scalable and lends significant pruning power without sacrificing the soundness of the result.

RDF datasets show that our techniques are much more scalable and efficient in correctly answering keyword search queries for realistic RDF workloads.         

EXISTING TECHNIQUE:-

Schema technique

PROPOSED TECHNIQUE: -

Backward search technique

TECHNIQUE DEFINITION:-

Keyword search returns answers that do not correspond to real sub graphs or misses valid matches from the Underlying RDF data

 Inability to scale to handle typical RDF datasets with tens of millions of triples.                    

TECHNIQUE DEFINITION:-

This technique uses different intuitions, which is more scalable and lends significant pruning power without sacrificing the soundness of the result.

 Benchmark and large real RDF datasets show that our techniques are much more scalable and efficient

Search.

DRAWBACK:-

Inability to scale to handle typical RDF datasets with tens of millions of triples.

Incorrect answers the keyword search returns answers.

ADVANTAGE:-

Correctly answering keyword search queries for realistic RDF workloads.

Correct answers the keyword search returns answers.