Continuous Join between Dynamic Query and Graph Stream |
Author(s): |
| Ms. Vaishali Gundu Powar , Department of Technology,Shivaji University,Kolhapur; Mr. Pradeep C. Bhaskar, Department of Technology,Shivaji University,Kolhapur |
Keywords: |
| NNT, NPVs, Dominant Vector Join Algorithm |
Abstract |
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Graph is widely used in various real applications such as social network modeling and chemical compound analysis. In many applications, graphs are often evolving along the time in a stream fashion instead of remaining static. These evolving graphs can be modeled as graph stream. The available work is proposed on static subgraph search. We proposed method to continuously join query stream and graph stream. Nodes neighborhood information is used as filtering feature to minimize candidates for join. Nearest Neighbor Trees are generated using neighborhood information. To minimize execution cost nearest neighbor trees are converted to numerical vectors. Proposed algorithms use Dominant vector and skyline join methods for stream join. Here we present comparative analysis on these two methods. |
Other Details |
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Paper ID: IJSRDV3I60568 Published in: Volume : 3, Issue : 6 Publication Date: 01/09/2015 Page(s): 1166-1169 |
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