An Approach To Find Frequent Pattern From Logs Using Modified Apriori Algorithm
 |
International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2019 by IJCTT Journal | ||
| Volume-67 Issue-5 |
||
| Year of Publication : 2019 | ||
| Authors : Priyanka Makkar | ||
| DOI : 10.14445/22312803/IJCTT-V67I5P117 |
MLA Style:Priyanka Makkar"An Approach To Find Frequent Pattern From Logs Using Modified Apriori Algorithm" International Journal of Computer Trends and Technology 67.5 (2019): 99-103.
APA Style:Priyanka Makkar (2019). An Approach To Find Frequent Pattern From Logs Using Modified Apriori Algorithm International Journal of Computer Trends and Technology, 67(5), 99-103.
Abstract
Web Usage Mining is an application of Data Mining to generates pattern from the logs which is created when user interacts with websites. Web usage mining is about processing or analysing clickstream data. We can analyse these logs and can find out the user interest and can recommend pages based on user interest. In this paper we have applied Modified Apriori Algorithm on web logs to find patterns. Logs are first pre-processed and then modified Apriori is applied to find interesting pattern which can be used to predict the next page visit of user. The Modified Apriori Algorithm is fast as it requires less scan of database than the basic Apriori algorithm. We have used the dummy dataset and find the frequent patterns using Modified Apriori Algorithm. Modified Apriori is faster as compared to basic Apriori Algorithm as it requires less database scan and therefore suitable for many real time applications.
Reference
[1] Pritish Yuvraj ,Suneetha K. R. ,” Modified Apriori Graph Algorithm for Frequent Pattern Mining”, 2016 International Conference on Innovations in information Embedded and Communication Systems (ICIIECS’16).
[2] Mobasher B., R. Cooley, J. Srivastava.” Automatic personalization based on web usage mining.”,Communications of ACM 43 142-151.
[3] Simmi Bagga, “ Ethos of Web Usage Mining - A Survey”, IJA-ERA)ISSN: 2454-2377 Volume – 2, Issue – 1, May – 2016.
[4] K.Harish Kumar , “A Study on Web Mining Types and Applications “, International Journal of Trend in Research and Development, Volume 3(5), ISSN: 2394-9333 www.ijtrd.com
[5] IOANA MOISIL, “Advanced AI Techniques for Web Mining”, Mathematical Methods, Computational Techniques, Non-LinearSystems, Intelligent Systems.
[6] Aggarwal, B. B. D. S., and Shivangi Dhall, "Web mining: Information and pattern discovery on the world wide web.", International Journal of Science, Technology & Management .
[7] Praveen Kumari, “Web Mining - Concept, Classification and Major Research Issues: A Review”, Asian J. Adv. Basic Sci.: 2016, 4(2), 41-44 ISSN (Print): 2454 – 7492 ISSN (Online): 2347 – 4114.
[8] Neha Sharma, “A Hand to Hand Taxonomical Survey on Web Mining”, International Journal of Computer Applications (0975 – 8887), Volume 60– No.3.
[9] J. Srivastava , P. Desikan , V. Kumar, ?”Web Mining – Concepts, Applications and Research Directions?”, Studies in Fuzziness and Soft Computing, Volume 180, pp. 275–307.
[10] Cyrus Shahabi,Farnoush Banaei-Kashani,” Efficient and Anonymous Web-Usage Mining for Web Personalization”, https://infolab.usc.edu/DocsDemos/informs.pdf.
[11] Cooley:l: Jaideep Srivastava t, Robert , Mukund Deshpande, Pang-Ning Tan,” Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data “,SIGKDD Explorations, Volume 1, Issue 2
[12] Rajinder Singh Rao, Jyoti Arora,” A Survey on Methods used in Web Usage Mining”, International Research Journal of Engineering and Technology (IRJET)
[13] Sahaj Chavda, Saurabh Jain, Nikunj Panchal, Manisha Valera,” Recent Trends and Novel Approaches in Web Usage Mining “,International Research Journal of Engineering and Technology (IRJET)
[14] Agrawal, R., Imielinski, T., and Swami, A. N,“Mining association rules between sets of items in large databases”, In Proceedings of the ACM SIGMOD International Conference on Management of Data, 207-216.
[15] K. R. Suneetha and Dr. R. Krishnamoorthi, “Identifying User Behaviour by Analyzing Web Server Access Log File”, IJCSNS International Journal of Computer Science and Network Security, VOL..9 No .4, April 2009.
[16] Rakesh Agrawal and Ramakrishnan Srikant, “Fast Algorithms for Mining Association Rules”, Proceedings of the 20th VLDB Conference Santiago, Chile, 1994.
[17] Han, J., Jian, Pei., Yiwen, Yin, and Runying, Mao. “Mining Frequent Pattern without Candidate Generation: A FrequentPattern Tree Approach”. Journal of Data Mining and Knowledge Discovery, 8, pp.53-87, 2004
Keywords
Pre-processing weblogs, web usage Mining, Modified Apriori algorithm, faster Apriori