Computer Science ›› 2019, Vol. 46 ›› Issue (4): 228-234.doi: 10.11896/j.issn.1002-137X.2019.04.036
• Artificial Intelligence • Previous Articles Next Articles
SU Chang, WU Peng-fei, XIE Xian-zhong, LI Ning
CLC Number:
[1]LI H,GE Y,ZHU H,et al.Point-of-Interest Recommendations:Learning Potential Checkins from Friends[C]∥In Proceedings of the 22nd ACM SIGKDD International Conference on Know-ledge Discovery and Data Mining.San Francisco:ACM Press,2016:975-984. [2]YU Y,WANG H,SUN S,et al.Exploiting location significance and user authority for point-of-interest recommendation[C]∥Advances in Knowledge Discovery and Data Mining- 21st Paci-fic-Asia Conference.South Korea:PAKDD Press,2017:119-130. [3]YANG S,HUANG G,XIANG Y,et al.Modeling User Preferences on Spatiotemporal Topics for Point-of-Interest Recommendation[C]∥IEEE International Conference on Services Computing.Honolulu:IEEE Press,2017:204-211. [4]LIM K H,CHAN J,LECKIE C,et al.Personalized trip recommendation for tourists based on user interests,points of interest visit durations and visit recency[J].Knowledge & Information Systems,2017(2):1-32. [5]XIE M,WANG S,WANG H,et al.Learning Graph-based POI Embedding for Location based Recommendation[C]∥ACM International on Conference on Information and Knowledge Mana-gement.Indianapolis:ACM,2016:15-24. [6]FANG M Y,DAI B R.Power of Bosom Friends,POI Recom- mendation by Learning Preference of Close Friends and Similar Users[C]∥Big Data Analytics and Knowledge Discovery.Porto:Springer Press,2016:179-192. [7]ZHANG J D,CHOW C Y,ZHENG Y.ORec:An Opinion-Based Point-of-Interest Recommendation Framework[C]∥ACM International on Conference on Information and Knowledge Mana-gement.Melbourne:ACM,2015:1641-1650. [8]YE M,YIN P,LEE W C,et al.Exploiting geographical influence for collaborative point-of-interest recommendation[C]∥Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval.Beijing:ACM Press,2011:325-334. [9]ZHANG J D,CHOW C Y,LI Y.iGeoRec:A Personalized and Efficient Geographical Location Recommendation Framework[J].IEEE Transactions on Services Computing,2015,8(5):701-714. [10]LI H,HONG R,ZHU S,et al.Point-of-Interest Recommender Systems:A Separate-Space Perspective[C]∥IEEE International Conference on Data Mining.Barcelona:IEEE Press,2016:231-240. [11]CHENG C,HUANG J,ZHONG N.Point-of-Interest Recommendations by Unifying Multiple Correlations[C]∥Web-Age Information Management.Nanchang:Springer Press,2016:178-190. [12]LIN K,WANG J,ZHANG Z,et al.Adaptive location recommendation algorithm based on location-based social networks[C]∥International Conference on Computer Science & Education.Cambridge:IEEE Press,2015:137-142. [13]WANG R Q,PAN J,LI Y X,Research on collaborative recommendation method based on multiple data sources of social network.Telecommunications Science[J].Telecommunications Science,2015,31(6):78-84.(in Chinese) 王瑞琴,潘俊,李一啸.基于多社交数据源的协同推荐方法研究[J].电信科学,2015,31(6):78-84. [14]HE M,XIAO R,LIU W S,et al.Collaborative Filtering Recommendation Algorithm Combing Category Information and User Interests [J].Telecommunications Science,2017,44(8):230-235.(in Chinese) 何明,肖润,刘伟世,等.融合类别信息和用户兴趣度的协同过滤推荐算法[J].计算机科学,2017,44(8):230-235. [15]Yelp.Challenge Data Set[OL].(2015-12-24).http://www.yelp.com/dataset_change. [16]ZHANG J D,CHOW C Y.GeoSoCa:Exploiting Geographical,Social and Categorical Correlations for Point-of-Interest Recommendations[C]∥Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval.Santiago:ACM Press,2015:443-452. |
[1] | CHENG Zhang-tao, ZHONG Ting, ZHANG Sheng-ming, ZHOU Fan. Survey of Recommender Systems Based on Graph Learning [J]. Computer Science, 2022, 49(9): 1-13. |
[2] | WANG Guan-yu, ZHONG Ting, FENG Yu, ZHOU Fan. Collaborative Filtering Recommendation Method Based on Vector Quantization Coding [J]. Computer Science, 2022, 49(9): 48-54. |
[3] | SUN Xiao-han, ZHANG Li. Collaborative Filtering Recommendation Algorithm Based on Rating Region Subspace [J]. Computer Science, 2022, 49(7): 50-56. |
[4] | CAI Xiao-juan, TAN Wen-an. Improved Collaborative Filtering Algorithm Combining Similarity and Trust [J]. Computer Science, 2022, 49(6A): 238-241. |
[5] | HE Yi-chen, MAO Yi-jun, XIE Xian-fen, GU Wan-rong. Matrix Transformation and Factorization Based on Graph Partitioning by Vertex Separator for Recommendation [J]. Computer Science, 2022, 49(6A): 272-279. |
[6] | GUO Liang, YANG Xing-yao, YU Jiong, HAN Chen, HUANG Zhong-hao. Hybrid Recommender System Based on Attention Mechanisms and Gating Network [J]. Computer Science, 2022, 49(6): 158-164. |
[7] | DONG Xiao-mei, WANG Rui, ZOU Xin-kai. Survey on Privacy Protection Solutions for Recommended Applications [J]. Computer Science, 2021, 48(9): 21-35. |
[8] | WANG Ying-li, JIANG Cong-cong, FENG Xiao-nian, QIAN Tie-yun. Time Aware Point-of-interest Recommendation [J]. Computer Science, 2021, 48(9): 43-49. |
[9] | ZHAN Wan-jiang, HONG Zhi-lin, FANG Lu-ping, WU Zhe-fu, LYU Yue-hua. Collaborative Filtering Recommendation Algorithm Based on Adversarial Learning [J]. Computer Science, 2021, 48(7): 172-177. |
[10] | SHAO Chao, SONG Shu-mi. Collaborative Filtering Recommendation Algorithm Based on User Preference Under Trust Relationship [J]. Computer Science, 2021, 48(6A): 240-245. |
[11] | WU Jian-xin, ZHANG Zhi-hong. Collaborative Filtering Recommendation Algorithm Based on User Rating and Similarity of Explicit and Implicit Interest [J]. Computer Science, 2021, 48(5): 147-154. |
[12] | XIAO Shi-tao, SHAO Ying-xia, SONG Wei-ping, CUI Bin. Hybrid Score Function for Collaborative Filtering Recommendation [J]. Computer Science, 2021, 48(3): 113-118. |
[13] | HAO Zhi-feng, LIAO Xiang-cai, WEN Wen, CAI Rui-chu. Collaborative Filtering Recommendation Algorithm Based on Multi-context Information [J]. Computer Science, 2021, 48(3): 168-173. |
[14] | HAN Li-feng, CHEN Li. User Cold Start Recommendation Model Integrating User Attributes and Item Popularity [J]. Computer Science, 2021, 48(2): 114-120. |
[15] | LI Kang-lin, GU Tian-long, BIN Chen-zhong. Multi-space Interactive Collaborative Filtering Recommendation [J]. Computer Science, 2021, 48(12): 181-187. |
|