A comparative study of location-based recommendation systems

Recent advancements in location-based recommendation system (LBRS) and the availability of online applications, such as Twitter, Instagram, Foursquare, Path, and Facebook have introduced new research challenges in the area of LBRS. Use of content, such as geo-tagged media, point location-based, and...

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Bibliographic Details
Published in:Knowledge engineering review 2017-01, Vol.32, Article e7
Main Authors: Rehman, Faisal, Khalid, Osman, Madani, Sajjad Ahmad
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Cold
Collaboration
Information retrieval
Information sources
Recommender systems
Social networks
Social research
Survey Article
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Summary:Recent advancements in location-based recommendation system (LBRS) and the availability of online applications, such as Twitter, Instagram, Foursquare, Path, and Facebook have introduced new research challenges in the area of LBRS. Use of content, such as geo-tagged media, point location-based, and trajectory-based information help in connecting the gap between the online social networking services and the physical world. In this article, we present a systematic review of the scientific literature of LBRS and summarize the efforts and contributions proposed in the literature. We have performed a qualitative comparison of the existing techniques used in the area of LBRS. We present the basic filtration techniques used in LBRS followed by a discussion on the services and the location features the LBRS utilizes to perform the recommendations. The classification of criteria for recommendations and evaluation metrics are also presented. We have critically investigated the techniques proposed in the literature for LBRS and extracted the challenges and promising research topics for future work.
ISSN:0269-8889
1469-8005
DOI:10.1017/S0269888916000308