Results 211 to 220 of about 243,536 (257)

Combination treatment for chronic insomnia disorder in adults: an American Academy of Sleep Medicine clinical practice guideline. [PDF]

J Clin Sleep Med
Buysse DJ, Arnedt JT, Buenaver L, Chang JL, Fernandez-Mendoza J, Patel SI, Zhou ES, Falck-Ytter Y, Hyer S, Kazmi U, Singh M, Wickwire EM.   +11 more
europepmc   +1 more source

CAPRI: Context-aware point-of-interest recommendation framework

Software Impacts
Ali Tourani, Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo   +3 more
openaire   +1 more source

Test the Child, Uncover the High-Risk Parent: A Call to Expand Universal Pediatric Lipid Screening. [PDF]

Am J Lifestyle Med
Hyman J, Doolittle B.
europepmc   +1 more source

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On successive point-of-interest recommendation

World Wide Web, 2018
With the increasing popularity of location-based social networks (LBSNs), users are able to share the Point-of-Interests (POIs) they visited by check-ins. By analyzing the users’ historical check-in records, POI recommendation can help users get better visiting experience by recommending POIs which users may be interested in. Although recent successive
Yi-Shu Lu, Wen-Yueh Shih, Hung-Yi Gau, Kuan-Chieh Chung, Jiun-Long Huang   +4 more
openaire   +1 more source

Point-of-Interest Recommendation With Global and Local Context

IEEE Transactions on Knowledge and Data Engineering, 2022
The task of point of interest (POI) recommendation aims to recommend unvisited places to users based on their check-in history. A major challenge in POI recommendation is data sparsity, because a user typically visits only a very small number of POIs among all available POIs. In this paper, we propose AUC-MF to address the POI recommendation problem by
Peng Han 0005, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng 0001, Xiangliang Zhang 0001   +5 more
openaire   +2 more sources

Time-aware point-of-interest recommendation

Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval, 2013
The availability of user check-in data in large volume from the rapid growing location based social networks (LBSNs) enables many important location-aware services to users. Point-of-interest (POI) recommendation is one of such services, which is to recommend places where users have not visited before. Several techniques have been recently proposed for
Quan Yuan 0001, Gao Cong, Zongyang Ma, Aixin Sun, Nadia Magnenat-Thalmann   +4 more
openaire   +2 more sources