DocumentCode :
8088
Title :
OmniSuggest: A Ubiquitous Cloud-Based Context-Aware Recommendation System for Mobile Social Networks
Author :
Khalid, Osman ; Khan, Muhammad Usman Shahid ; Khan, Samee U. ; Zomaya, Albert Y.
Author_Institution :
North Dakota State Univ., Fargo, ND, USA
Volume :
7
Issue :
3
fYear :
2014
fDate :
July-Sept. 2014
Firstpage :
401
Lastpage :
414
Abstract :
The evolution of mobile social networks and the availability of online check-in services, such as Foursquare and Gowalla, have initiated a new wave of research in the area of venue recommendation systems. Such systems recommend places to users closely related to their preferences. Although venue recommendation systems have been studied in recent literature, the existing approaches, mostly based on collaborative filtering, suffer from various issues, such as: 1) data sparseness, 2) cold start, and 3) scalability. Moreover, many existing schemes are limited in functionality, as the generated recommendations do not consider group of “friends” type situations. Furthermore, the traditional systems do not take into account the effect of real-time physical factors (e.g., distance from venue, traffic, and weather conditions) on recommendations. To address the aforementioned issues, this paper proposes a novel cloud-based recommendation framework OmniSuggest that utilizes: 1) Ant colony algorithms, 2) social filtering, and 3) hub and authority scores, to generate optimal venue recommendations. Unlike existing work, our approach suggests venues at a finer granularity for an individual or a “group” of friends with similar interest. Comprehensive experiments are conducted with a large-scale real dataset collected from Foursquare. The results confirm that our method offers more effective recommendations than many state of the art schemes.
Keywords :
ant colony optimisation; cloud computing; information filtering; mobile computing; social networking (online); Foursquare; Gowalla; OmniSuggest system; ant colony algorithms; authority score; hub score; mobile social networks; social filtering; ubiquitous cloud-based context-aware recommendation system; venue recommendation systems; Collaboration; Data models; Filtering; Mobile communication; Real-time systems; Scalability; Social network services; Recommendation framework; cloud-framework; group recommendation; mobile social networks;
fLanguage :
English
Journal_Title :
Services Computing, IEEE Transactions on
Publisher :
ieee
ISSN :
1939-1374
Type :
jour
DOI :
10.1109/TSC.2013.53
Filename :
6678350
Link To Document :
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