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Survey on Detecting Users Behavior Applying Country- Wise Local Search

Abhishek Shukla, Gajendra Singh Dhakad

Abstract


In this paper we have discussed about the data mining, web mining and the recommendation network. Web mining is explained with the classification of web mining. Recommendater system is explained properly with the explanation of whole procedure of the recommendater system. Various sequential mining pattern algorithms have been explained with various pros and cons. Also, all the work that has been done by them till date is explained fully with proper explanation.

Cite this Article
Abhishek Shukla, Gajendra Singh Dhakad. Survey on Detecting Users
Behavior Applying Country-Wise Local Search. Journal of Advanced Database
Management & Systems. 2015; 2(3):11–19p.


Keywords


Sequential pattern mining, web mining, recommendation system

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References


Fayyad UM, Shapiro GP, Smyth P, From Data Mining to Knowledge Discovery in Databases. 0738-4602-1996, AI Magazine (Fall 1996). 37–53p.

Han J, Kamber M, Data Mining: Concepts and Techniques. Second edition Morgan Kaufmann Publishers, 2006.

Pani SK, Panigrahy L, Sankar VH, et al. Web Usage Mining: A Survey on Pattern Extraction from Web Logs, Int J Instru Control Automat. 2011; 1(1): 15–23p.

Eirinaki M, Vazirgiannis M, Web Mining for Web Personalization, ACM T Internet Technol. 2003; 3(1): 1–27p.

Dunham MH, Data Mining Introductory and Advanced Topics. Pearson Education, 2003.

Mobasher B, Dai H, Luo T, et al. Effective Personalization based on Association Rule Discovery from Web Usage Data, Proc. of the 3rd ACM Workshop on Web Information and Data Management (WIDM01), New York, NY, USA, 2001, 9–15p.

Perkowitz M Etzioni O, Towards adaptive Web sites: Conceptual Framework and Case Study, Artif Intell. 2000; 118: 245–275p.

Jalali M, Mustapha N, Mamat A, et al. OPWUMP an Architecture for Online Predicting in WUM-based Personalization System, In 13th International CSI Computer Science, Springer Verlag, 2008.

p.

Agrawal R, Srikant R, Mining Sequential Patterns, In Proceedings of International Conference on Data Engineering. Taipei, Mar 1995, 3–14p.

Minghua Zhang, Ben Kao, Chi-Lap Yip, et al. A GSP-based Efficient Algorithm for Mining Frequent Sequences, Proc. of IC-AI, 2001, 1–5p.

Ayres J, Gehrke J, Yiu T, et al. Sequential Pattern Mining using a Bitmap Representation, Proceedings of ACM SIGKDD ’02, NY, USA, July 2002, 429–435p.

Zaki M, SPADE: An Efficient Algorithm for Mining Frequent Sequences, Kluwer Academic Publisher’s Machine Learning, 2001; 42: 31–60p.

Han J, Pei J, Mortazavi-Asl B, et al. FreeSpan: Frequent Pattern projected Sequential Pattern Mining, Proc. ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (SIGKDD ’00), NY, USA, Aug. 2000, 355–359p.

Pei J, Han J, Mortazavi-Asl B, et al. PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth, Proc. Int’l Conf. Data Engineering (ICDE ’01), Apr. 2001, 215–224p.

Pasquier N, Bastide Y, Taouil R, et al. Discovering Frequent Closed Itemsets for Association Rules, 7th Int’l Conf. on Database Theory, Jan. 1999, 398–416p.

Grahne G, Zhu JF, Fast Algorithm for Frequent Itemset Mining using FP-Trees, IEEE T Knowl Data Eng. 2005; 17(10): 1347–1362p.

Pei J, Han J, Mao R, CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets, Proceedings of ACM DMKD ’00, Dallas, TX, May 2000, 21–30p.

Zaki M, Hsiao C, CHARM: An Efficient Algorithm for Closed Itemset Mining, Proceedings of SIAM’s SDM ’02, Apr. 2002, 457–473p.

Wang J, Han J, Pei J, CLOSET+: Searching for the Best Strategies for

Mining Frequent Closed Itemsets, Proceedings of ACM SIGKDD’03, Aug.

, 236–245p.

Yan X, Han J, Afshar R, CloSpan: Mining Closed Sequential Patterns in Large Databases, Proceedings of SIAM’s SDM ’03, May 2003, 166–177p.

Wang J, Han J, Chun Li, Frequent Closed Sequence Mining without Candidate Maintenance, IEEE TKDE, Aug. 2007; 19(8): 1042–1056p.

Nancy P. Lin, Wei-Hua Hao, Hung-Jen Chen, et al. Fast Mining of Closed Sequential Patterns, WSEAS T Comp. Mar. 2008; 7(3): 133–139p.

Mahdi Esmaeili, Fazekas Gabor, Finding Sequential Patterns from Large Sequence Data, IJCSI Int J Comp Sci Issue, 7(1, 1), January 2010, ISSN (Online): 1694-0784 ISSN (Print): 1694-0814.

Qiankun Zhao, Sourav S. Bhowmick, Sequential Pattern Mining: A Survey, Technical Report, CAIS, Nanyang Technological University, Singapore, No.2003118, 2003.

Dipa Dixit, Jayant Gadge, Automatic Recommendation for Online Users Using Web Usage Mining, Int J Manag Info Technol (IJMIT). August 2010; 2(3): 33–42p.

Vijayalakshmi S, Mohan V, Suresh Raja S, Mining Of Users’ Access Behaviour For Frequent Sequential Pattern From Web Logs, Int J Database Manage Syst (IJDMS). August 2010; 2(3): 31–45p.

Niti Desai, Amit Ganatra, Sequential Pattern Mining Methods: A Snap Shot, IOSR J Comp Eng. (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727, (Mar. -Apr. 2013); 10(4): 12–20p.

Rajashree Shettar, Sequential Pattern Mining From Web Log Data, Int J Eng Sci Adv Technol. 2012; 2(2): 204–208p, ISSN: 2250–3676.

Jian Pei, Jiawei Han, Behzad Mortazaviasl, et al. Mining Access Patterns Efficiently from Web Logs, Natural Sciences and Engineering Research Council of Canada (grant NSERC-A3723), the Networks of Centres of Excellence of Canada (grant NCE/IRIS-3), and the

Hewlett-Packard Lab.

Pragya Rajput, Joy Bhattacharjee, Roopali Soni, A Proposed Framework to Implicit Measures of User Interests through Country and Predicting Users’ Future Requests in WWW, Int J Soft Comput Eng

(IJSCE). ISSN: 2231-2307, March 2013; 3(1): 340–343p.

Purushothama Raju V, Saradhi Varma GP, A Novel Algorithm For Mining Closed Sequential Patterns, Int J Data Mining Know Manage Process (IJDKP). January 2015; 5(1): 41–50p.


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