Effective Bin Rank for Scaling Dynamic Authority Based Search with Materialized Sub Graphs
L. Prasanna Kumar
L. Prasanna Kumar, Asso. Prof., Department of CSE, Dadi Institute of Engineering & Technology, Visakhapatnam, India.
Manuscript received on July 21, 2014. | Revised Manuscript received on August 10, 2014. | Manuscript published on August 30, 2014. | PP: 21-23 | Volume-3 Issue-6, August 2014. | Retrieval Number: F3265083614/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Dynamic authority-based keyword search algorithms, such as Object Rank and personalized Page Rank, leverage semantic link information to provide high quality, high recall search in databases, and the Web. Conceptually, these algorithms require a query time Page Rank-style iterative computation over the full graph. In this paper we introduce Bin Rank system which approximates Object Rank results by utilizing a hybrid approach inspired by materialized views in traditional query processing.
Keywords: World Wide Web, Object Rank, sub graphs, Bin Rank.