A new classification model for online predicting users' future movements
Nowadays many internet users prefer to navigate their interest web pages in special web site rather than navigating all web pages in the web site. For this reason some techniques have been developed for predicting user’s future requests. Data manning algorithms can be applied to many prediction prob...
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2008
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/69196/1/A%20new%20classification%20model%20for%20online%20predicting%20users%27%20future%20movements.pdf |
| _version_ | 1825933673035202560 |
|---|---|
| author | Jalali, Mehrdad Mustapha, Norwati Mamat, Ali Sulaiman, Md. Nasir |
| author_facet | Jalali, Mehrdad Mustapha, Norwati Mamat, Ali Sulaiman, Md. Nasir |
| author_sort | Jalali, Mehrdad |
| collection | UPM |
| description | Nowadays many internet users prefer to navigate their interest web pages in special web site rather than navigating all web pages in the web site. For this reason some techniques have been developed for predicting user’s future requests. Data manning algorithms can be applied to many prediction problems. We can exploit Web Usage Mining for Knowledge extracting based on user behavior during the web navigation. The WUM applies data mining techniques for extracting knowledge from user log files in the particular web server. The WUM can model user behavior and, therefore, to forecast their future movements by mining user navigation patterns. To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. The prediction of users’ future movements by this manner can improve accuracy of recommendations. |
| first_indexed | 2024-03-06T10:00:57Z |
| format | Conference or Workshop Item |
| id | upm.eprints-69196 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:00:57Z |
| publishDate | 2008 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-691962019-06-12T07:37:03Z http://psasir.upm.edu.my/id/eprint/69196/ A new classification model for online predicting users' future movements Jalali, Mehrdad Mustapha, Norwati Mamat, Ali Sulaiman, Md. Nasir Nowadays many internet users prefer to navigate their interest web pages in special web site rather than navigating all web pages in the web site. For this reason some techniques have been developed for predicting user’s future requests. Data manning algorithms can be applied to many prediction problems. We can exploit Web Usage Mining for Knowledge extracting based on user behavior during the web navigation. The WUM applies data mining techniques for extracting knowledge from user log files in the particular web server. The WUM can model user behavior and, therefore, to forecast their future movements by mining user navigation patterns. To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. The prediction of users’ future movements by this manner can improve accuracy of recommendations. IEEE 2008 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69196/1/A%20new%20classification%20model%20for%20online%20predicting%20users%27%20future%20movements.pdf Jalali, Mehrdad and Mustapha, Norwati and Mamat, Ali and Sulaiman, Md. Nasir (2008) A new classification model for online predicting users' future movements. In: 3rd International Symposium on Information Technology (ITSim'08), 26-28 Aug. 2008, Kuala Lumpur, Malaysia. . 10.1109/ITSIM.2008.4631852 |
| spellingShingle | Jalali, Mehrdad Mustapha, Norwati Mamat, Ali Sulaiman, Md. Nasir A new classification model for online predicting users' future movements |
| title | A new classification model for online predicting users' future movements |
| title_full | A new classification model for online predicting users' future movements |
| title_fullStr | A new classification model for online predicting users' future movements |
| title_full_unstemmed | A new classification model for online predicting users' future movements |
| title_short | A new classification model for online predicting users' future movements |
| title_sort | new classification model for online predicting users future movements |
| url | http://psasir.upm.edu.my/id/eprint/69196/1/A%20new%20classification%20model%20for%20online%20predicting%20users%27%20future%20movements.pdf |
| work_keys_str_mv | AT jalalimehrdad anewclassificationmodelforonlinepredictingusersfuturemovements AT mustaphanorwati anewclassificationmodelforonlinepredictingusersfuturemovements AT mamatali anewclassificationmodelforonlinepredictingusersfuturemovements AT sulaimanmdnasir anewclassificationmodelforonlinepredictingusersfuturemovements AT jalalimehrdad newclassificationmodelforonlinepredictingusersfuturemovements AT mustaphanorwati newclassificationmodelforonlinepredictingusersfuturemovements AT mamatali newclassificationmodelforonlinepredictingusersfuturemovements AT sulaimanmdnasir newclassificationmodelforonlinepredictingusersfuturemovements |