Web page recommendation model for web personalization
Web usage mining has gained more popularity among researchers in discovering the users browsing behavior mining the web server log that records all the users transactions activities. In this paper, we developed a usage model for predictions based on association rule. Similarity between items contain...
| Main Authors: | , |
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| Format: | Book Section |
| Language: | English |
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Springer Berlin / Heidelberg
2004
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| Subjects: | |
| Online Access: | http://eprints.utm.my/9802/1/AbdulMananAhmad2004_web_page_recommendation_model_for_web_personalization.pdf |
| _version_ | 1825910381476839424 |
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| author | Ahmad, Abdul Manan Ahmad Hijazi, Mohd. Hanafi |
| author_facet | Ahmad, Abdul Manan Ahmad Hijazi, Mohd. Hanafi |
| author_sort | Ahmad, Abdul Manan |
| collection | ePrints |
| description | Web usage mining has gained more popularity among researchers in discovering the users browsing behavior mining the web server log that records all the users transactions activities. In this paper, we developed a usage model for predictions based on association rule. Similarity between items contained in the active user profile will be calculated upon the matched rules and finally the top-N most similar items are then recommended to the user. We used the time spent on each page for weighting the pages instead of binary. Two evaluation metrics were applied to evaluate the accuracy of the recommendations, namely precision and coverage. |
| first_indexed | 2024-03-05T18:16:13Z |
| format | Book Section |
| id | utm.eprints-9802 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:16:13Z |
| publishDate | 2004 |
| publisher | Springer Berlin / Heidelberg |
| record_format | dspace |
| spelling | utm.eprints-98022010-06-02T02:03:34Z http://eprints.utm.my/9802/ Web page recommendation model for web personalization Ahmad, Abdul Manan Ahmad Hijazi, Mohd. Hanafi QA75 Electronic computers. Computer science Web usage mining has gained more popularity among researchers in discovering the users browsing behavior mining the web server log that records all the users transactions activities. In this paper, we developed a usage model for predictions based on association rule. Similarity between items contained in the active user profile will be calculated upon the matched rules and finally the top-N most similar items are then recommended to the user. We used the time spent on each page for weighting the pages instead of binary. Two evaluation metrics were applied to evaluate the accuracy of the recommendations, namely precision and coverage. Springer Berlin / Heidelberg 2004-10-14 Book Section PeerReviewed application/pdf en http://eprints.utm.my/9802/1/AbdulMananAhmad2004_web_page_recommendation_model_for_web_personalization.pdf Ahmad, Abdul Manan and Ahmad Hijazi, Mohd. Hanafi (2004) Web page recommendation model for web personalization. In: Knowledge-Based Intelligent Information and Engineering Systems. Lecture Notes in Computer Science, 3214/2 . Springer Berlin / Heidelberg, pp. 587-593. ISBN 978-3-540-23206-3 http://dx.doi.org/10.1007/b100910 DOI : 10.1007/b100910 |
| spellingShingle | QA75 Electronic computers. Computer science Ahmad, Abdul Manan Ahmad Hijazi, Mohd. Hanafi Web page recommendation model for web personalization |
| title | Web page recommendation model for web personalization |
| title_full | Web page recommendation model for web personalization |
| title_fullStr | Web page recommendation model for web personalization |
| title_full_unstemmed | Web page recommendation model for web personalization |
| title_short | Web page recommendation model for web personalization |
| title_sort | web page recommendation model for web personalization |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/9802/1/AbdulMananAhmad2004_web_page_recommendation_model_for_web_personalization.pdf |
| work_keys_str_mv | AT ahmadabdulmanan webpagerecommendationmodelforwebpersonalization AT ahmadhijazimohdhanafi webpagerecommendationmodelforwebpersonalization |