Using Web Log Files the Comparative Study of Big Data with Map Reduce Technique

This research paper, discusses, how the implementations of a planned algorithm will be processed. The data set is collected from one of the engineering colleges in India. The Datasets are collected from different sources and how the raw data is a preprocessor. The data set is analyzed by using the Map Reducing Technique and that should carry out in naive byes and KNN algorithm. The Map-Reduce technique is parallel to computation using the key/value pair. Thus, the Map-Reduce system helps to analyze the information which will give the data of the potential clients, such as, login time, credit value, and a lot more at least reaction time. Finally, execution estimation has been done by using ROC bend to discover and affirm which algorithm is best similarly as orchestrating the weblog records per the general time, the specific time they have taken on a specific website. The Naive Bayes algorithm if its anticipated characterization. Like that the same process in the KNN algorithm. It is basic to perceive which the greatest classifier method is. To carry out this, the foreseen outcomes are approved during (ROC) Receiver Operating Characteristic curves.

[1]  Taghi M. Khoshgoftaar,et al.  A survey of open source tools for machine learning with big data in the Hadoop ecosystem , 2015, Journal of Big Data.

[3]  Hazem H. Refai,et al.  Adaptive D2D resources allocation underlaying (2-tier) heterogeneous cellular networks , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[4]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[5]  Dr.ANTONY Selvadoss Thanamani V.Chitraa.  An Enhanced Clustering Technique for Web Usage Mining , 2012 .

[6]  Paul HernIrene Garrig.  Modeling Web logs to enhance the analysis of Web usage data , 2010 .

[7]  P. Iswarya.  Predictive Analysis of Users Behaviour in Web Browsing and Pattern Discovery Networks , 2014 .

[8]  A study on English teaching improvement based on stakeholders' needs and wants: the case of the Faculty of International Tourism of the Macau University of Science and Technology (MUST). , 2012 .

[9]  Avneet Saluja,et al.  Web Usage Mining Approaches for User ’ s Request Prediction : A Survey , 2015 .

[10]  Arvind K. Sharma.  Enhancing the Performance of the Website through Web Log Analysis and Improvement , 2012 .

[11]  Mudassir Khan,et al.  Big Data Analytics Evaluation , 2018 .

[12]  K Savitha,et al.  Mining of Web Server Logs in a Distributed Cluster Using Big Data Technologies , 2014 .

[13]  R. Shanthi,et al.  An Efficient Web Mining Algorithm To Mine Web Log Information , 2022 .

[14]  Yan Liu,et al.  A cloud service architecture for analyzing big monitoring data , 2016 .

[15]  Pablo E. Román,et al.  Identifying web sessions with simulated annealing , 2014, Expert Syst. Appl..

[16]  S. Saravanan,et al.  Analyzing Large Web Log Files in a Hadoop Distributed Cluster Environment , 2014 .

[17]  Pooja Pawar,et al.  Web Log based Analysis of User's Browsing Behavior , 2015 .

[18]  M. Ramesh,et al.  A comparative study of various clustering techniques on big data sets using Apache Mahout , 2016, 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC).

[19]  K. Sudheer Reddy,et al.  An effective data preprocessing method for Web Usage Mining , 2013, 2013 International Conference on Information Communication and Embedded Systems (ICICES).

[20]  Songtao Zheng,et al.  Naïve Bayes Classifier: A MapReduce Approach , 2014 .

[21]  Joseph A. Issa.  Performance Evaluation and Estimation Model Using Regression Method for Hadoop WordCount , 2015, IEEE Access.

[22]  Sayalee Narkhede,et al.  HMR Log Analyzer: Analyze Web Application Logs Over Hadoop MapReduce , 2013 .