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تحسين أداء الأنظمة الناصحة
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الأنظمة الناصحة هي الأنظمة التي تساعد المستخدمين على اختيار العناصر الأكثر ملائمة من مجموعة كبيرة من العناصر و ذلك اعتمادا على أذواقهم و اهتماماتهم. أصبحت مثل هذه الأنظمة واحدة من أقوى الأدوات المستخدمة في مواقع التجارة الإلكترونية و مواقع التواصل الاجتماعي. على الرغم من ذلك فإن استخدام هذه الأنظمة في مواقع التجارة الإلكترونية يواجه العديد من التحديات مثل: الإقلاع البارد, قابلية التوسع و الشعب. في هذه الورقة قمنا بتقديم حل لمشكلة الإقلاع البارد, وقمنا بالمقارنة بين عدة خوارزميات لقواعد الربط و ذلك لاختيار الخوارزمية الأفضل لحل مشكلتي قابلية التوسع و التشعب.
Recommendation systems are the systems thathelp users to select suitable items from a large collection of items based on their tastes and interests. Such systems have become one of the most powerful tools in electronic commerce and social websites. Nonetheless , using these systems in e-commerce websites faces many drawbacks such as: cold start-up, scalability and sparsity. In this paper, we present a solution to cold-start-up problem, and compare between many association rule algorithms to select the most suitable one to solve the scalability and sparsity problems.
References used
Barshe corel, M. Bassam ,A 2014- An Improved Apriori Algorithm for Association Rules. IRJCSA, vol 7. 26-48
DUPING ,P. GAO ,Y 2010- A New Improvement of Apriori Algorithm for Mining Association Rules. ICCASM ), vol 9. 300-324
Hall, M. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten ,T 2013 The WEKA data mining software: an update. SIGKDD Explorationsvol 13.400- 415
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