کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6872834 1440624 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A self-adaptive point-of-interest recommendation algorithm based on a multi-order Markov model
ترجمه فارسی عنوان
یک الگوریتم توصیه ی خودپنداره ای بر مبنای یک مدل چند منظوره مارکوف
کلمات کلیدی
خدمات مبتنی بر مکان، نقطه مورد علاقه، سیستم توصیه شده، زنجیره مارکوف، نفوذ توالی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی
As one of the personalization technologies, point-of-interest (POI) recommendation systems have attracted more and more attention from academic and industrial researchers. Exploiting the spatio-temporal pattern of users check-ins for user modeling is the core content of the current research of POI recommendation in location-based social networks (LBSNs). In this paper, we propose a POI recommendation algorithm based on a multi-order Markov model, which predicts users next favorite POIs based not only on their current location but also on their previous location, and propose a self-adaptive algorithm to adjust our multi-order Markov model to be available to all users check-ins. Moreover, to improve the precision of our proposed POI recommendation algorithm, we incorporate the geographical influence and temporal popularity of users checked-in POIs into our proposed algorithm. Finally, experimental results on two real datasets demonstrate that our proposed algorithm outperforms the state-of-the-art POI recommendation methods in terms of F−measure@N(N=5,10,15,20).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Future Generation Computer Systems - Volume 89, December 2018, Pages 506-514
نویسندگان
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