Investigation of Heterogeneous Approach to Fact Invention of Web Users’ Web Access Behaviour
DOI:
https://doi.org/10.24297/jac.v12i22.118Keywords:
pattern discovery, preprocessing, web usage mining, web rating, web review, web ranking.Abstract
World Wide Web consists of a huge volume of different types of data. Web mining is one of the fields of data mining wherein there are different web services and a large number of web users. Web user mining is also one of the fields of web mining. The web users’ information about the web access is collected through different ways. The most common technique to collect information about the web users is through web log file. There are several other techniques available to collect web users’ web access information; they are through browser agent, user authentication, web review, web rating, web ranking and tracking cookies. The web users find it difficult to retrieve their required information in time from the web because of the huge volume of unstructured and structured information which increases the complexity of the web. Web usage mining is very much important for various purposes such as organizing website, business and maintenance service, personalization of website and reducing the network bandwidth. This paper provides an analysis about the web usage mining techniques. Â
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References
1. Duhan N., Sharma A. K., and Bhatia K. K., “Page ranking algorithms: a surveyâ€, in Proc. IEEE International Advance Computing Conference, pp. 1530-1537, 2009.doi: 10.1109/IADCC.2009.4809246
2. Facca F. M. and P. L. Lanzi, “Mining interesting knowledge from weblogs: a surveyâ€, in Proc. Data and Knowledge Engineering, vol. 53 issue 3, pp. 225-241, 2005. doi:10.1016/j.datak.2004.08.001
3. Baoyao Z., Siu C. and Alvis C., Fong M. “An Effective Approach for Periodic Web Personalization,“, in Proceedings of the IEEE/ACM International Conference on Web Intelligence. IEEE, 2006. doi: 10.1109/WI.2006.36
4. Pooja Kherwa and Jyotsna Nigam,†Data Preprocessing: A Milestone of Web Usage Mining†in International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 4, Issue 2, 2015. doi: 10.1007/978-3-540-88081-3_7-Springer
5. Ciesielski V. and Lalani A., “Data mining of web access logs from an academic web siteâ€, in Design and application of hybrid intelligent systems, pg. 1034-1043, 2003. doi : 10.1145/951440.951443
6. Sharma A.,â€NY Web Usage Mining: Data Preprocessing, Pattern Discovery and Pattern Analysis on the RIT Web Dataâ€, in Rochester Institute of Technology, 2008. doi: 10.1007/978-3-540-88081-3_7-Springer.
7. Mohammad A. and Soukaena H.,â€Adding new level in KDD to make the usage mining more efficientâ€, National Information Technology Symposium (NITS 2006), pp. 131-140, 2006. doi : 10.1186/s40537-014-0007-7
8. Youquan H., â€Decentralized Association Rule Mining On Web using Rough Set Theory†in Journal of communication and computer ,vol. 2, no. 7, 2005. doi : 10.1.1.86.311
9. Castellano G., Fanelli A. and Torsello M., â€Log Data Preparation for Mining Web Usage Patternâ€, IADIS International Conference Applied Computing, pp. 371-378, 2007. doi :10.1.1.109.4423
10. Tan. P, and Kumar, †Discovery of Web Robot Sessions Based on their Navigational Patternsâ€, in Data Mining and Knowledge Discovery, vol. 6 no. 1, pp. 9-35, 2002. doi:10.1023/A:1013228602957
11. Kushmeric N., â€Learning To Remove Internet Advertisements, “in Third Annual Conf. on Autonomous Agents. 1999. doi:10.1145/301136.301186.
12. Joshila G., Maheswari V. and Dhinaharan N.,â€Web Log Data Analysis and Mining†in Proc CCSIT-2011, Springer CCIS, Vol 133, pp 459-469, 2011. doi : 10.1007/978-3-642-17881-8_44
13. Cooley R., Mobasher B., Srivastava J., “Knowledge and Information Systemâ€, in Springer-Verlag, 1999. doi : 10.1007/BF03325089.
14. Chen J., Sun L., Zaiane O. and Goebel. R., “Visualizing and Discovering Web Navigational Patternsâ€, in Seventh International Workshop on the Web and Databases, 2004. doi : 10.1007/978-3-540-88081-3_7-Springer.
15. Suresh R. and Padmajavalli. R., â€An overview of Data Preprocessing in Data and Web Usage miningâ€, in IEEE International Conference, pg. 193-198, 2006. doi : 10.1109/ICDIM.2007.369352
16. Cooley R., Mobasher B. and Srivastava J.,â€Web Mining: Information and Pattern Discovery on the world wide webâ€, in IEEE International Conference on Tools With Artificial Intelligence, pp. 558-567, 1997. doi: 10.1109/TAI.1997.632303
17. Istvan K. Nagy and Csaba G., â€User Behaviour Analysis Based On Time Spent On Web Pages: Web Mining Application in E-Commerce and E-Servicesâ€, in Studies in Computational Intelligence, 2009, Volume172/2009, pg. 117-36, doi: 10.1007/978-3-540-88081-3_7-Springer.
18. Ivancsy R., and Juhasz S., â€Analysis of Web User Identification Methodsâ€, in World Academy of Science, Engineering and Technology, vol: 1, 2007. doi :10.1287/ijoc.15.2.171.14445.
19. Morzy T., Wojcie M., and Zakrazewicz M., â€Web Use Clustering†in International Symposium on Computer and Information Sciences, pp. 374–382, 2000. doi : 10.1145/1081706.1081733.
20. Spilopoulou M., Mobasher B., Berendt B. and Nakagawa M,.â€A Framework for the Evaluation of Session Reconstruction Heuristics in Web Usage Analysisâ€, in INFORMS Journal On Computing, vol. 15, no. 2, 2003. doi: 10.12691/ajss-3-2-1.
21. Yan L, Boqin F. and Qinjiao M., “Research on Path Completion Technique in Web Usage Miningâ€, in IEEE International Symposium on Computer Science and Computational Technology, 2008. doi : 10.1109/ISCSCT.2008.151
22. Michal Munk and Martin DrlÃk, “Impact of Different Pre-Processing Tasks on Effective Identification of Users’ Behavioral Patterns in Web-based Educational System,†Proceedings of the International Conference on Computational Science, vol. 4, pp. 1640-1649, 2011. doi:10.1016/j.procs.2011.04.177
23. Robert F., Dell P., Roman E., and Juan D., “Web User Session Reconstruction Using Integer Programmingâ€, in IEEE/ACM International Conference on Web Intelligence and Intelligent Agent, vol. 1, pp. 385-388, 2008. doi : 10.1109/WIIAT.2008.181
24. Jose M. Domenech and Javier L., “A Tool for Web Usage Mining†8th International Conference on Intelligent Data Engineering and Automated Learning, pp 695-704, 2007. doi : 10.1007/978-3-540-77226-2_70
25. Catlegde L. and Pitkow J., “Characterizing browsing behaviors in the world wide Webâ€, in Computer Networks and ISDN systems, vol. 27, no. 6, 1995. doi :10.1016/0169-7552(95)00043-7
26. Chitraa V. and Dr. Antony Selvadoss Davamani, â€An Efficient Path Completion Technique for web log miningâ€, in IEEE International Conference on Computational Intelligence and Computing Research, 2010. doi : 10.1007/978-3-540-88081
27. Ismail H. and Toroslu M., â€Graph Theoretic Approach for Session Reconstruction Problemâ€, in Information Sciences: an International Journal, vol. 177, no. 6, pp. 1523-1529, 2007. doi : 10.1016/j.ins.2006.05.004
28. Aruna Kumari G. K. and Sudheer Shetty, â€Web Usage Mining: Web log Pre-processing and Online Visitor’s frequent Pattern Discoveryâ€, in International Journal of Innovative Research in Computer and Communication Engineering, vol. 4, no. 4, 2016. doi : 10.15680/IJIRCCE.2016. 0404149
29. Dipa Dixit and Kiruthika M., “Preprocessing Of Web Logsâ€, in International Journal on Computer Science and Engineering, vol. 2 no. 7, pp. 2447-2452, 2010. doi : 10.1.1.301.8554
30. Tasawar Hussain, Sohail Asghar and Nayyer Masood,†Web usage mining: A survey on preprocessing of web log file†IEEE Xplore, 2010. doi : 10.1109/ICIET.2010.5625730
31. Berendt B. and Spiliopoulou. M., “Analyzing navigation behavior in Web sites integrating multiple information systems.†in VLDB Journal on Databases and the Web, vol. 9, no. 1, pp. 56-75, 2000. doi : 10.1007/s007780050083
32. Aldekhail M., “Application and Significance of Web Usage Mining in the 21st Century: A Literature Reviewâ€, in International Journal of Computer Theory and Engineering, vol. 8, no. 1, pp. 41-47, 2016. doi : 10.7763/IJCTE.2016.V8.1017
33. Aarti Parekh, Anjali Patel, Sonal Parmar and Prof. Vaishali Patel, " Web usage Mining : Frequent Pattern Generation using Association Rule Mining and Clustering," in International Journal of Engineering Research & Technology, vol. 4, no. 4, pp. 1243-1246, 2014. doi : 10.17577/IJERTV4IS041467
34. Khushbu Patel, Anurag Punde, Kavita Namdev, Rudra Gupta and Mohit Vyas†Detailed Study of Web Mining Approaches-A Survey†in International Journal of Engineering Sciences & Research Technology, pp. 23-30, 2015, doi : 10.1.1.91.1602. 13
35. Pierrakos D., G. Paliouras, C. Papatheodorou, and C. D. Spyropoulos, "Web usage mining as a tool for personalization: A survey," in User Modeling and User-Adapted Interaction, vol. 13, pp. 311-372, 2003. doi : 10.1023/A:1026238916441
36. Moushumi Sharma, Ajit Das and Nibedita Roy, " A Complete Survey on Association Rule Mining and Its Improvement ", in International Journal of Instrumentation, Control & Automation (IJICA), vol. 4, no. 5, pp. 9335-9341, 2016.
37. Chitraa and Thavamani A. S., "An enhanced clustering technique for web usage mining", in International Journal of Engineering Research & Technology (IJERT), vol. 1, pp. 5, 2012. doi :10.1.1.680.4122.
38. Srivastava J., Cooley R., Deshpande M., and Tan P. N., "Web usage mining: Discovery and applications of usage patterns from web data," in ACM SIGKDD, vol. 1, 2000. doi : 10.1.1.110.432.
39. Lokeshkumar R., Sindhuja R. and Dr. P. Sengottuvelan, " A Survey on Preprocessing of Web Log File in Web Usage Mining", in International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 8, 2014. DOI: 10.1109/IV.2008.40.
40. Sajid N. A, S. Zafar, and S. Asghar, "Sequential pattern finding: A survey", in Proc. International Conference on Information and Emerging Technologies (ICIET), pp. 1-6, 2010 doi: 10.1109/ICIET.2010.5625726
41. Ramakrishnan Srikant and Rakesh Agrawal, â€Mining Sequential Patterns: Generalizations and Performance Improvements†in Advances in Database Technology - EDBT '96, vol. 1057, pp. 1-17, 1996. doi: 10.1007/BFb0014140
42. Wei Shen, Jianyong Wang and Jiawei Han, â€Sequential Pattern Mining†in Frequent Pattern Mining, pp. 261-282, 2014. doi : 10.1007/978-3-319-07821-2_11
43. Philippe Fournier-Viger, Ted Gueniche, Souleymane Zida, Vincent S. Tseng Jozef K, Michal M and Martin D, â€ERMiner: Sequential Rule Mining Using Equivalence Classesâ€, in Advances in Intelligent Data Analysis XIII, vol. 8819, pp. 108-119, 2014. doi : 10.1007/978-3-319-12571-8_10
44. Mohamed Koutheaïr Khribi, Mohamed Jemni and Olfa Nasraoui, †Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval†in IEEE International Conference on Advanced Learning Technologies, 2008. doi: 10.1109/ICALT.2008.198
45. Bharat Bhushan Agarwal and Dr. Mahmoodul Hasan Khan, †An Improving Web Page Ranking based on Visit of Links with Time Factor and Cursor Movement Algorithm†in International Journal of Advanced Research in Computer and Communication Engineering, vol. 5, no. 1, pp. 83-86, 2016. doi : 10.17148/IJARCCE.2016.5119
46. Jiang Li and Peter Willett, †ArticleRank: a PageRankâ€based alternative to numbers of citations for analysing citation networks†in Aslib Journal of Information Management, vol. 61, no. 6, pp. 605-618, 2009. doi : 10.1108/00012530911005544
47. Hema Dubey and Prof. B. N. Roy,â€An Improved Page Rank Algorithm Based on Optimized Normalization Technique†in International Journal of Computer Science and Information Technology, vol. 2, no. 5 pp-2183-2188, 2011. doi : 10.1.1.228.938
48. Neelam Tyagi and Sharma,†Weighted Page Rank Algorithm Based on Number of Visits of Links of Web Page†in International Journal of Soft Computing and Engineering, vol. 2, no. 3, pp. 441-446, 2012. doi: 10.1.1.458.5810
49. Bing L., Bu J., Chen C. and Qiu G., â€Opinion word expansion and target extraction through double propagation†in Computer Linguistics, vol. 37, no. 1, pp-9-27, 2011. doi:10.1162/coli_a_00034
50. Jeonghee Yi, Tetsuya Nasukawa, Razvan Bunescu and Wayne Niblack, â€Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques†in IEEE International Conference on Data Mining : ICDM, pp.427, 2003. doi:10.1145/245108.245122
51. Chen. L, Qi. L and Wang. F, â€Comparison of feature-level learning methods for mining online consumer reviews†in Expert System with Applications, vol. 39, no. 10, pp. 9588-9601, 2012. doi : 10.1016/j.eswa.2012.02.158
52. Xianghua. F, Guo. L, Yanyan. G and Zhiqiang W, â€Multi-aspect sentiment analysis for Chinese online social review based on topic modelling and HowNet lexicon†in Knowledge Based Systems, vol. 37, pp. 186-195, 2013. doi : 10.1016/j.knosys.2012.08.003
53. Hua Xu, Weiwei Yang and Jiushuo Wang, †Hierarchical emotion classification and emotion component analysis on chinese micro-blog posts†in Expert Systems with Applications: An International Journal, vol. 42, no. 22, pp. 8745-8752, 2015. doi : 10.1016/j.eswa.2015.07.028
54. Hu. M and Liu. B, â€Mining opinion features in customer reviews†in National Conference on Artificial Intelligence, pp. 755-760, 2004. doi : 10.1016/0306-4573(90)90014-S
55. Shengchung ding and Ting Jiang,†Comment Target Extraction Based on Conditional Random Field & Domain Ontology†in International Conference on Asian Language Processing, pp. 189-192, 2010. doi:10.1109/IALP.2010.81
56. Wang H., Tsou B. K., Zhu J., Zhu M. and Ma M., â€Aspects-based opinion polling from customer reviews†in IEEE Transactions on Affective Computing, vol. 2, no. 1, pp. 37-49, 2011. doi:10.1109/T-AFFC.2011.2
57. Erdem Ucar, Erdinc Uzun and Pınar Tufekci†A novel algorithm for extracting the user reviews from web pages†in Journal of Information Science, vol. 42, no. 5, 2016. doi: 10.1177/0165551516666446
58. Martin Emmert and Florian Meier†An Analysis of Online Evaluations on a Physician Rating Website: Evidence From a German Public Reporting Instrument†in Journal of Medical Internet Research, vol. 15, no. 8, 2016. doi:10.2196/jmir.2655
59. Patel S., Cain R., Neailey K. and Hooberman L. †Exploring Patients’ Views Toward Giving Web-Based Feedback and Ratings to General Practitioners in England: A Qualitative Descriptive Study†in Journal of Medical Internet Research, vol. 18, no. 8, 2016. doi: 10.2196/jmir.5865
2. Facca F. M. and P. L. Lanzi, “Mining interesting knowledge from weblogs: a surveyâ€, in Proc. Data and Knowledge Engineering, vol. 53 issue 3, pp. 225-241, 2005. doi:10.1016/j.datak.2004.08.001
3. Baoyao Z., Siu C. and Alvis C., Fong M. “An Effective Approach for Periodic Web Personalization,“, in Proceedings of the IEEE/ACM International Conference on Web Intelligence. IEEE, 2006. doi: 10.1109/WI.2006.36
4. Pooja Kherwa and Jyotsna Nigam,†Data Preprocessing: A Milestone of Web Usage Mining†in International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 4, Issue 2, 2015. doi: 10.1007/978-3-540-88081-3_7-Springer
5. Ciesielski V. and Lalani A., “Data mining of web access logs from an academic web siteâ€, in Design and application of hybrid intelligent systems, pg. 1034-1043, 2003. doi : 10.1145/951440.951443
6. Sharma A.,â€NY Web Usage Mining: Data Preprocessing, Pattern Discovery and Pattern Analysis on the RIT Web Dataâ€, in Rochester Institute of Technology, 2008. doi: 10.1007/978-3-540-88081-3_7-Springer.
7. Mohammad A. and Soukaena H.,â€Adding new level in KDD to make the usage mining more efficientâ€, National Information Technology Symposium (NITS 2006), pp. 131-140, 2006. doi : 10.1186/s40537-014-0007-7
8. Youquan H., â€Decentralized Association Rule Mining On Web using Rough Set Theory†in Journal of communication and computer ,vol. 2, no. 7, 2005. doi : 10.1.1.86.311
9. Castellano G., Fanelli A. and Torsello M., â€Log Data Preparation for Mining Web Usage Patternâ€, IADIS International Conference Applied Computing, pp. 371-378, 2007. doi :10.1.1.109.4423
10. Tan. P, and Kumar, †Discovery of Web Robot Sessions Based on their Navigational Patternsâ€, in Data Mining and Knowledge Discovery, vol. 6 no. 1, pp. 9-35, 2002. doi:10.1023/A:1013228602957
11. Kushmeric N., â€Learning To Remove Internet Advertisements, “in Third Annual Conf. on Autonomous Agents. 1999. doi:10.1145/301136.301186.
12. Joshila G., Maheswari V. and Dhinaharan N.,â€Web Log Data Analysis and Mining†in Proc CCSIT-2011, Springer CCIS, Vol 133, pp 459-469, 2011. doi : 10.1007/978-3-642-17881-8_44
13. Cooley R., Mobasher B., Srivastava J., “Knowledge and Information Systemâ€, in Springer-Verlag, 1999. doi : 10.1007/BF03325089.
14. Chen J., Sun L., Zaiane O. and Goebel. R., “Visualizing and Discovering Web Navigational Patternsâ€, in Seventh International Workshop on the Web and Databases, 2004. doi : 10.1007/978-3-540-88081-3_7-Springer.
15. Suresh R. and Padmajavalli. R., â€An overview of Data Preprocessing in Data and Web Usage miningâ€, in IEEE International Conference, pg. 193-198, 2006. doi : 10.1109/ICDIM.2007.369352
16. Cooley R., Mobasher B. and Srivastava J.,â€Web Mining: Information and Pattern Discovery on the world wide webâ€, in IEEE International Conference on Tools With Artificial Intelligence, pp. 558-567, 1997. doi: 10.1109/TAI.1997.632303
17. Istvan K. Nagy and Csaba G., â€User Behaviour Analysis Based On Time Spent On Web Pages: Web Mining Application in E-Commerce and E-Servicesâ€, in Studies in Computational Intelligence, 2009, Volume172/2009, pg. 117-36, doi: 10.1007/978-3-540-88081-3_7-Springer.
18. Ivancsy R., and Juhasz S., â€Analysis of Web User Identification Methodsâ€, in World Academy of Science, Engineering and Technology, vol: 1, 2007. doi :10.1287/ijoc.15.2.171.14445.
19. Morzy T., Wojcie M., and Zakrazewicz M., â€Web Use Clustering†in International Symposium on Computer and Information Sciences, pp. 374–382, 2000. doi : 10.1145/1081706.1081733.
20. Spilopoulou M., Mobasher B., Berendt B. and Nakagawa M,.â€A Framework for the Evaluation of Session Reconstruction Heuristics in Web Usage Analysisâ€, in INFORMS Journal On Computing, vol. 15, no. 2, 2003. doi: 10.12691/ajss-3-2-1.
21. Yan L, Boqin F. and Qinjiao M., “Research on Path Completion Technique in Web Usage Miningâ€, in IEEE International Symposium on Computer Science and Computational Technology, 2008. doi : 10.1109/ISCSCT.2008.151
22. Michal Munk and Martin DrlÃk, “Impact of Different Pre-Processing Tasks on Effective Identification of Users’ Behavioral Patterns in Web-based Educational System,†Proceedings of the International Conference on Computational Science, vol. 4, pp. 1640-1649, 2011. doi:10.1016/j.procs.2011.04.177
23. Robert F., Dell P., Roman E., and Juan D., “Web User Session Reconstruction Using Integer Programmingâ€, in IEEE/ACM International Conference on Web Intelligence and Intelligent Agent, vol. 1, pp. 385-388, 2008. doi : 10.1109/WIIAT.2008.181
24. Jose M. Domenech and Javier L., “A Tool for Web Usage Mining†8th International Conference on Intelligent Data Engineering and Automated Learning, pp 695-704, 2007. doi : 10.1007/978-3-540-77226-2_70
25. Catlegde L. and Pitkow J., “Characterizing browsing behaviors in the world wide Webâ€, in Computer Networks and ISDN systems, vol. 27, no. 6, 1995. doi :10.1016/0169-7552(95)00043-7
26. Chitraa V. and Dr. Antony Selvadoss Davamani, â€An Efficient Path Completion Technique for web log miningâ€, in IEEE International Conference on Computational Intelligence and Computing Research, 2010. doi : 10.1007/978-3-540-88081
27. Ismail H. and Toroslu M., â€Graph Theoretic Approach for Session Reconstruction Problemâ€, in Information Sciences: an International Journal, vol. 177, no. 6, pp. 1523-1529, 2007. doi : 10.1016/j.ins.2006.05.004
28. Aruna Kumari G. K. and Sudheer Shetty, â€Web Usage Mining: Web log Pre-processing and Online Visitor’s frequent Pattern Discoveryâ€, in International Journal of Innovative Research in Computer and Communication Engineering, vol. 4, no. 4, 2016. doi : 10.15680/IJIRCCE.2016. 0404149
29. Dipa Dixit and Kiruthika M., “Preprocessing Of Web Logsâ€, in International Journal on Computer Science and Engineering, vol. 2 no. 7, pp. 2447-2452, 2010. doi : 10.1.1.301.8554
30. Tasawar Hussain, Sohail Asghar and Nayyer Masood,†Web usage mining: A survey on preprocessing of web log file†IEEE Xplore, 2010. doi : 10.1109/ICIET.2010.5625730
31. Berendt B. and Spiliopoulou. M., “Analyzing navigation behavior in Web sites integrating multiple information systems.†in VLDB Journal on Databases and the Web, vol. 9, no. 1, pp. 56-75, 2000. doi : 10.1007/s007780050083
32. Aldekhail M., “Application and Significance of Web Usage Mining in the 21st Century: A Literature Reviewâ€, in International Journal of Computer Theory and Engineering, vol. 8, no. 1, pp. 41-47, 2016. doi : 10.7763/IJCTE.2016.V8.1017
33. Aarti Parekh, Anjali Patel, Sonal Parmar and Prof. Vaishali Patel, " Web usage Mining : Frequent Pattern Generation using Association Rule Mining and Clustering," in International Journal of Engineering Research & Technology, vol. 4, no. 4, pp. 1243-1246, 2014. doi : 10.17577/IJERTV4IS041467
34. Khushbu Patel, Anurag Punde, Kavita Namdev, Rudra Gupta and Mohit Vyas†Detailed Study of Web Mining Approaches-A Survey†in International Journal of Engineering Sciences & Research Technology, pp. 23-30, 2015, doi : 10.1.1.91.1602. 13
35. Pierrakos D., G. Paliouras, C. Papatheodorou, and C. D. Spyropoulos, "Web usage mining as a tool for personalization: A survey," in User Modeling and User-Adapted Interaction, vol. 13, pp. 311-372, 2003. doi : 10.1023/A:1026238916441
36. Moushumi Sharma, Ajit Das and Nibedita Roy, " A Complete Survey on Association Rule Mining and Its Improvement ", in International Journal of Instrumentation, Control & Automation (IJICA), vol. 4, no. 5, pp. 9335-9341, 2016.
37. Chitraa and Thavamani A. S., "An enhanced clustering technique for web usage mining", in International Journal of Engineering Research & Technology (IJERT), vol. 1, pp. 5, 2012. doi :10.1.1.680.4122.
38. Srivastava J., Cooley R., Deshpande M., and Tan P. N., "Web usage mining: Discovery and applications of usage patterns from web data," in ACM SIGKDD, vol. 1, 2000. doi : 10.1.1.110.432.
39. Lokeshkumar R., Sindhuja R. and Dr. P. Sengottuvelan, " A Survey on Preprocessing of Web Log File in Web Usage Mining", in International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 8, 2014. DOI: 10.1109/IV.2008.40.
40. Sajid N. A, S. Zafar, and S. Asghar, "Sequential pattern finding: A survey", in Proc. International Conference on Information and Emerging Technologies (ICIET), pp. 1-6, 2010 doi: 10.1109/ICIET.2010.5625726
41. Ramakrishnan Srikant and Rakesh Agrawal, â€Mining Sequential Patterns: Generalizations and Performance Improvements†in Advances in Database Technology - EDBT '96, vol. 1057, pp. 1-17, 1996. doi: 10.1007/BFb0014140
42. Wei Shen, Jianyong Wang and Jiawei Han, â€Sequential Pattern Mining†in Frequent Pattern Mining, pp. 261-282, 2014. doi : 10.1007/978-3-319-07821-2_11
43. Philippe Fournier-Viger, Ted Gueniche, Souleymane Zida, Vincent S. Tseng Jozef K, Michal M and Martin D, â€ERMiner: Sequential Rule Mining Using Equivalence Classesâ€, in Advances in Intelligent Data Analysis XIII, vol. 8819, pp. 108-119, 2014. doi : 10.1007/978-3-319-12571-8_10
44. Mohamed Koutheaïr Khribi, Mohamed Jemni and Olfa Nasraoui, †Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval†in IEEE International Conference on Advanced Learning Technologies, 2008. doi: 10.1109/ICALT.2008.198
45. Bharat Bhushan Agarwal and Dr. Mahmoodul Hasan Khan, †An Improving Web Page Ranking based on Visit of Links with Time Factor and Cursor Movement Algorithm†in International Journal of Advanced Research in Computer and Communication Engineering, vol. 5, no. 1, pp. 83-86, 2016. doi : 10.17148/IJARCCE.2016.5119
46. Jiang Li and Peter Willett, †ArticleRank: a PageRankâ€based alternative to numbers of citations for analysing citation networks†in Aslib Journal of Information Management, vol. 61, no. 6, pp. 605-618, 2009. doi : 10.1108/00012530911005544
47. Hema Dubey and Prof. B. N. Roy,â€An Improved Page Rank Algorithm Based on Optimized Normalization Technique†in International Journal of Computer Science and Information Technology, vol. 2, no. 5 pp-2183-2188, 2011. doi : 10.1.1.228.938
48. Neelam Tyagi and Sharma,†Weighted Page Rank Algorithm Based on Number of Visits of Links of Web Page†in International Journal of Soft Computing and Engineering, vol. 2, no. 3, pp. 441-446, 2012. doi: 10.1.1.458.5810
49. Bing L., Bu J., Chen C. and Qiu G., â€Opinion word expansion and target extraction through double propagation†in Computer Linguistics, vol. 37, no. 1, pp-9-27, 2011. doi:10.1162/coli_a_00034
50. Jeonghee Yi, Tetsuya Nasukawa, Razvan Bunescu and Wayne Niblack, â€Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques†in IEEE International Conference on Data Mining : ICDM, pp.427, 2003. doi:10.1145/245108.245122
51. Chen. L, Qi. L and Wang. F, â€Comparison of feature-level learning methods for mining online consumer reviews†in Expert System with Applications, vol. 39, no. 10, pp. 9588-9601, 2012. doi : 10.1016/j.eswa.2012.02.158
52. Xianghua. F, Guo. L, Yanyan. G and Zhiqiang W, â€Multi-aspect sentiment analysis for Chinese online social review based on topic modelling and HowNet lexicon†in Knowledge Based Systems, vol. 37, pp. 186-195, 2013. doi : 10.1016/j.knosys.2012.08.003
53. Hua Xu, Weiwei Yang and Jiushuo Wang, †Hierarchical emotion classification and emotion component analysis on chinese micro-blog posts†in Expert Systems with Applications: An International Journal, vol. 42, no. 22, pp. 8745-8752, 2015. doi : 10.1016/j.eswa.2015.07.028
54. Hu. M and Liu. B, â€Mining opinion features in customer reviews†in National Conference on Artificial Intelligence, pp. 755-760, 2004. doi : 10.1016/0306-4573(90)90014-S
55. Shengchung ding and Ting Jiang,†Comment Target Extraction Based on Conditional Random Field & Domain Ontology†in International Conference on Asian Language Processing, pp. 189-192, 2010. doi:10.1109/IALP.2010.81
56. Wang H., Tsou B. K., Zhu J., Zhu M. and Ma M., â€Aspects-based opinion polling from customer reviews†in IEEE Transactions on Affective Computing, vol. 2, no. 1, pp. 37-49, 2011. doi:10.1109/T-AFFC.2011.2
57. Erdem Ucar, Erdinc Uzun and Pınar Tufekci†A novel algorithm for extracting the user reviews from web pages†in Journal of Information Science, vol. 42, no. 5, 2016. doi: 10.1177/0165551516666446
58. Martin Emmert and Florian Meier†An Analysis of Online Evaluations on a Physician Rating Website: Evidence From a German Public Reporting Instrument†in Journal of Medical Internet Research, vol. 15, no. 8, 2016. doi:10.2196/jmir.2655
59. Patel S., Cain R., Neailey K. and Hooberman L. †Exploring Patients’ Views Toward Giving Web-Based Feedback and Ratings to General Practitioners in England: A Qualitative Descriptive Study†in Journal of Medical Internet Research, vol. 18, no. 8, 2016. doi: 10.2196/jmir.5865
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Published
2016-12-15
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Manohar, E., & Punithavathani, D. (2016). Investigation of Heterogeneous Approach to Fact Invention of Web Users’ Web Access Behaviour. JOURNAL OF ADVANCES IN CHEMISTRY, 12(22), 5424–5436. https://doi.org/10.24297/jac.v12i22.118
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All articles published in Journal of Advances in Linguistics are licensed under a Creative Commons Attribution 4.0 International License.
