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|3 10.33948/0584-026-001-003
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|a eng
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|b السعودية
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| 100 |
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|9 524573
|a Kuppusamy, K. S.
|e Author
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| 245 |
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|a Caseper: An Efficient Model For Personalized Web Page Change Detection Based On Segmentation
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|b جامعة الملك سعود
|c 2014
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| 300 |
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|a 19 - 27
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|a بحوث ومقالات
|b Article
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|b Users who visit a web page repeatedly at frequent intervals are more interested in knowing the recent changes that have occurred on the page than the entire contents of the web page. Because of the increased dynamism of web pages, it would be difficult for the user to identify the changes manually. This paper proposes an enhanced model for detecting changes in the pages, which is called CaSePer (Change detection based on Segmentation with Personalization). The change detection is micro managed by introducing web page segmentation. The web page change detection process is made efficient by having it perform a dual-step process. The proposed method reduces the complexity of the change detection by focusing only on the segments in which the changes have occurred. The user-specific personalized change detection is also incorporated in the proposed model. The model is validated with the help of a prototype implementation. The experiments conducted on the prototype implementation confirm a 77.8% improvement and a 97.45% accuracy rate.
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| 653 |
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|a تكنولوجيا المعلومات
|a صفحات الويب
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| 692 |
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|b Web Page Change Detection
|b Web Page Segmentation
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| 700 |
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|9 524574
|a Aghila, G.
|e Co-Author
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| 773 |
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|c 003
|e Journal of King Saud University (Computer and Information Sciences)
|f Maǧalaẗ ǧamʼaẗ al-malīk Saud : ùlm al-ḥasib wa al-maʼlumat
|l 001
|m مج26, ع1
|o 0584
|s مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
|v 026
|x 1319-1578
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| 856 |
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|u 0584-026-001-003.pdf
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| 930 |
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|d y
|p y
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| 995 |
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|a science
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| 999 |
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|c 973004
|d 973004
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