Chinatown / New York / Beijing / Los Angeles / home city / New York City / querying city / /
Company
E. Cho S.A. / Location-Based Social Networks / Intel / /
Country
United States / /
Currency
USD / / /
Event
Product Recall / Product Issues / /
Facility
Chinese restaurant / University Ours PCF Precision Users / Italian restaurant / University of Minnesota / /
IndustryTerm
proposed candidate selection algorithm / similarity computing operations / average online efficiency / online recommendation / online user behavior / online recommendation scenario / recommendation systems / baseline solutions / food hunters / online recommendation part / candidate selection algorithm / long-distance travel / travel sequences / recommender systems / travel recommendations / mean food / generic location recommendation systems / social networking services / association rule mining technique / food / collaborative social networking service / wireless communication technologies / online part / user similarity computing / online recommendations / collaborative filtering-based location recommender systems / Web personalization expert / personalized recommendation systems / travel expert / travel routes / online recommendation process / online selection / social networks / computing / social network / candidate select algorithm / preference-aware candidate selection algorithm / /
OperatingSystem
Windows 7 / /
Organization
National Science Foundation / IDF / University of Minnesota / Minneapolis / VLDB Endowment / US Federal Reserve / Department of Computer Science & Engineering / Ubiquitous Intelligence / /
Person
Mohamed Sarwat / G. Cong / Chi-Yin Chow / J. Levandoski / X. Cao / Selection / Mohamed F. Mokbel / Jie Bao / Justin Levandoski / C.S. Jensen / Ahmed Eldawy / /
Position
travel guide / first author / author / model each category group / Candidate / Cao / /
Product
MBR Spatial Range Location Recommender Spatial Range Precision / criteria / method increases / precision+ / /
ProvinceOrState
New Jersey / Louisiana / /
PublishedMedium
Journal of the ACM / Communications of the ACM / /
Technology
RAM / proposed candidate selection algorithm / API / GPS / mobile devices / ISDN / later preference-aware candidate selection algorithm / Xeon CPU 2.80GHz processor / candidate selection algorithm / wireless communication technologies / candidate select algorithm / preference-aware candidate selection algorithm / /
Location-based and Preference-Aware Recommendation Using Sparse Geo-Social Networking Data Jie Bao1 ∗ 1 Yu Zheng2