V. Jayaraj ¹, J. Jegathesh Amalraj ¹, V. Mathimalar ¹

Affiliations
1 Bharathidasan University, Tamilnadu, IN

Abstract

For efficient transformation of information, Routing is needed. The requirement of quality constraints have been increased due to the variety of applications involved. This has escort to eminence conscious routing. An updated network structure is required to maintain efficient routing. This paper endow with different methods that act upon topology discovery and route formulation, along with route maintenance. The topology discovery is performed initially by discovering the neighbors and then clustering them and assigning leaders for each cluster. The route formulation phase finds multiple paths to a node, and finally optimization is performed using a modified form of Tabu Search. The route maintenance is performed by periodically checking the available routes for invalid nodes and updating them. The proposed research work gives a complete strategy for topology discovery along with dynamic routing and it performs well under all circumstances in an Ad Hoc network.

Keywords

Topology Discovery, Tabu Search, Routing, Clustering, SENCAST

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V. Jayaraj ¹, V. Mahalakshmi ¹

Affiliations
1 Department of Computer Science and Engineering, Bharathidasan University, Tiruchirappalli – 620024, Tamil Nadu, IN

Abstract

Background: A novel algorithm named Information Retrieval configuration file is proposed to extract useful information from a set of resumes during extraction where the information gained is relevant and efficient for business needs. Methods: Manual analysis of this unstructured textual data is impractical, so numerous text mining methods are being developed to automate the process of analyzing this unstructured data employs a new technique named Weighted Ranking method. Result: The efficiency of recruitment process is improved while retrieving the information from the unstructured data. Application: In firms to improves the scope of the recruitment process using text mining algorithm to mine the data.

Keywords

Business Intelligence, Recruitment Process, Resume Mining, Text Mining

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