TY - GEN
T1 - Social-aware KNN search in location-based social networks
AU - Hu, Huiqi
AU - Feng, Jianhua
AU - Liu, Sitong
AU - Zhu, Xuan
PY - 2014
Y1 - 2014
N2 - Location-based social network services have become widely available on mobile devices. It not only helps users to strengthen their social connections, but also provides useful information. An appealing application of using these information is helping users to find proper objects(points of interests) nearby with friends' visiting experiences. In this paper, we define friend based K nearest neighbor(F-KNN) query, which aims at finding objects near the query location as well as receiving high evaluations from user's friends. To answer F-KNN query efficiently, we propose a hybrid index called F-Quadtree index, which effectively combines the geographic coordinates of objects and user's evaluation. We develop an efficient searching algorithm on the index. To further accelerate the querying process, we refine the algorithm with user based partition and memory materialization. Experimental studies on real data sets show that our methods achieve high performance.
AB - Location-based social network services have become widely available on mobile devices. It not only helps users to strengthen their social connections, but also provides useful information. An appealing application of using these information is helping users to find proper objects(points of interests) nearby with friends' visiting experiences. In this paper, we define friend based K nearest neighbor(F-KNN) query, which aims at finding objects near the query location as well as receiving high evaluations from user's friends. To answer F-KNN query efficiently, we propose a hybrid index called F-Quadtree index, which effectively combines the geographic coordinates of objects and user's evaluation. We develop an efficient searching algorithm on the index. To further accelerate the querying process, we refine the algorithm with user based partition and memory materialization. Experimental studies on real data sets show that our methods achieve high performance.
UR - https://www.scopus.com/pages/publications/84958545278
U2 - 10.1007/978-3-319-08010-9_27
DO - 10.1007/978-3-319-08010-9_27
M3 - 会议稿件
AN - SCOPUS:84958545278
SN - 9783319080093
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 242
EP - 254
BT - Web-Age Information Management - 15th International Conference, WAIM 2014, Proceedings
PB - Springer Verlag
T2 - 15th International Conference on Web-Age Information Management, WAIM 2014
Y2 - 16 June 2014 through 18 June 2014
ER -