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An Item based Geo-Recommender System Inspired by Artificial Immune Algorithms
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نویسنده
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Cabanas-Abascal Antonio ,García-Machicado Eduardo ,Prieto-González Lisardo ,Seco Antonio de Amescua
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منبع
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journal of universal computer science - 2013 - دوره : 19 - شماره : 13 - صفحه:2013 -2033
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چکیده
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Nowadays, one of the most relevant features provided by in almost every web site is a recommender system. however, they are usually focused on the common characteristics of several items which are shared among the users without taking into account that there are other very important features, such as geo-position. to face this lack of such relevant factors, authors propose the usage of a useful system that will aid in tasks related to pattern detection and fast adaptability to changes: artificial immune system. a combination of both systems and the addition of a geographic component will provide a new solution to this problem, which will solve as well these issues as other ones like comparison tasks in big data.
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کلیدواژه
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Recommender Systems ,Artificial Immune Systems ,Geo-localization ,Item ,Big data
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آدرس
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University Carlos III Madrid, Computer Science Department, Spain, University Carlos III Madrid, Computer Science Department, Spain, University Carlos III Madrid, Computer Science Department, Spain, University Carlos III Madrid, Computer Science Department, Spain
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پست الکترونیکی
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antonio.amescua@uc3m.es
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Authors
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