International Journal of Advanced Networking and Applications

Prabhat Kumar Sahu ¹, Rajendra Gupta ²

Affiliations
1 Research Scholar, Rabindranath Tagore University, Bhopal, IN
2 Rabindranath Tagore University, Bhopal, IN

Abstract

The web mining is a broad research area emerging to solve the issues that arise due to the WWW phenomenon. The Web mining research is a converging research area from several research communities, such as Databases, Information Retrieval and Artificial Intelligence. This work overview the most important issue of Web mining, namely sequential traversal patterns mining. In this paper, calculation of Weight and Support of every page is checked to know the importance of the web page and applied the Frequent Sequential Traversal Pattern Mining with Self Organizing Map (FSTSOM) algorithm. The performance of the proposed algorithm shows that the complete set of patterns runs considerably faster as compared to WAP Tree and FS-Tree algorithms.

Keywords

Pattern Mining, Web Page Prediction.

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GD Deshmukh ¹, Rajendra Gupta ²

Affiliations
1 Research Scholar, Rabindranath Tagore University, Bhopal., IN
2 Associate Professor, Dept. of Computer Science, Rabindranath Tagore University, Bhopal., IN

Abstract

The field of operations research models known as multi-criteria analysis, also known as Multi-Criteria DecisionMaking or Multi-Criteria Satisfaction Analysis deals with the process of making decisions when there are numerous objectives. The conflicting criteria, incomparable units, and challenges in designing/selecting alternatives are all aspects of these methods, which can manage both quantitative and qualitative criteria. The MUSA approach is an ordinal regression analysis-based preference disaggregation model. Based on their values and expressed preferences, the integrated methodology assesses the level of satisfaction of faculty at engineering institutions. The MUSA approach aggregates the various preferences in special satisfaction functions using data from satisfaction surveys. The paper presents a faculty performance analysis by implementing optimization technique known as PSO on Multi Criteria Satisfaction Analysis and shown performance analysis.

Keywords

MUSA, PSO, MUOMUSA, Optimization Technique.

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