夏立新, 杨金庆, 程秀峰. 移动环境下融合情境信息的群组推荐模型研究——基于用户APP行为数据的实证分析[J]. 情报学报, 2018, 37(4): 384-393.
Xia Lixin, Yang Jinqing, Cheng Xiufeng. Study of a Group Recommendation Model of Integrating Context Information in a Mobile Environment—Empirical Analysis Based on User APP Behavior Data. 情报学报, 2018, 37(4): 384-393.
[1] 吴丽花, 刘鲁. 个性化推荐系统用户建模技术综述[J]. 情报学报, 2006, 25(1): 55-62. [2] Chen Y L, Cheng L C, Chuang C N.A group recommendation system with consideration of interactions among group members[J]. Expert Systems with Applications, 2008, 34(3): 2082-2090. [3] 李岱峰, 覃正. 一种基于资源多属性分类的群组推荐模型[J]. 统计与决策, 2010(8): 153-155. [4] 金涛, 谢瑾奎, 杨宗源. 社交网络中快速群组生成及群组推荐研究[J]. 小型微型计算机系统, 2017, 38(3): 483-488. [5] Dey A K.Understanding and using context[J]. Personal and Ubiquitous Computing, 2001, 5(1): 4-7. [6] Kagita V R, Pujari A K, Padmanabhan V.Virtual user approach for group recommender systems using precedence relations[J]. Information Sciences, 2015, 194: 15-30. [7] Yu Z, Zhou X, Hao Y, et al.TV program recommendation for multiple viewers based on user profile merging[J]. User Modeling and User-Adapted Interaction, 2006, 16(1): 63-82. [8] Quijano-Sanchez L, Recio-Garcia J A, Diaz-Agudo B. An architecture and functional description to integrate social behaviour knowledge into group recommender systems[J]. Applied Intelligence, 2014, 40(4): 732-748. [9] Pessemier T, Dooms S, Martens L.Comparison of group recommendation algorithms[J]. Multimedia Tools and Applications, 2014, 72(3): 2497-2541. [10] Boratto L, Carta S.The rating prediction task in a group recommender system that automatically detects groups: architectures, algorithms, and performance evaluation[J]. Journal of Intelligent Information Systems, 2015, 45(2): 1-25 [11] O’Connor M, Dan C, Konstan J A, et al. PolyLens: a recommender system for groups of users[C]// Proceedings of the European Conference on Computer Supported Cooperative Work. Kluwer Academic Publishers, 2001: 199-218. [12] Baltrunas L, Makcinskas T, Ricci F.Group recommendations with rankaggregation and collaborative filtering[C]// Proceedings of the Fourth ACM Conference on Recommender Systems (RecSys), 2010: 26-30. [13] Berkovsky S, Freyne J.Group-based recipe recommendations: analysis of data aggregation strategies[C]// Proceedings of the Fourth ACM Conference on Recommender Systems. New York: ACM Press, 2010: 111-118. [14] Resnick P, Iacovou N, Suchak M, et al.GroupLens: an open architecture for collaborative filtering of netnews[C]// Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work. New York: ACM Press, 1994: 175-186. [15] 吴丽花, 刘鲁. 个性化推荐系统用户建模技术综述[J]. 情报学报, 2006, 25(1): 55-62. [16] Ricci F, Rokach L, Shapira B.Introduction to recommender systems handbook[M]// Recommender Systems Handbook. Boston: Springer, 2011: 1-35. [17] Adomavicius G, Tuzhilin A.Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6): 734-749. [18] Su X Y, Khoshgoftaar T M. A survey of collaborative filtering techniques[J]. Advances in Artificial Intelligence, 2009, 2009: Article No. 4. [19] Masthoff J.Group recommender systems: combining individual models[M]// Recommender Systems Handbook. Boston: Springer, 2011: 677-702. [20] McCarthy J F, Anagnost T D. MusicFX: an arbiter of group preferences for computer supported collaborative workouts[C]// Proceedings of the 1998 ACM Conference on Computer Supported Cooperative Work. New York: ACM Press, 1998: 363-372. [21] Yu Z, Zhou X, Hao Y, et al.TV program recommendation for multiple viewers based on user profile merging[J]. User Modeling and User-Adapted Interaction, 2006, 16(1): 63-82. [22] 胡伟健, 陈俊, 李灵芳, 等. 结合用户特征和兴趣变化的组推荐系统算法研究[J]. 软件导刊, 2016, 15(6): 60-62. [23] Adomavicius G.Incorporating contextual information in recommender systems using a multidimensional approach[J]. ACM Transactions on Information Systems, 2005, 23(1): 103-145. [24] Anand S S, Mobasher B.Contextual recommendation[C]// Proceedings of the Workshop on Web Mining, from Web to Social Web: Discovering and Deploying User and Content Profiles. Berlin: Springer-Verlag, 2007: 142-160. [25] 洪亮, 冉从敬, 吴志强. 移动环境下基于共同兴趣的情境感知信息推荐研究[J]. 情报理论与实践, 2014, 37(11): 124-128. [26] 夏立新, 杨金庆, 程秀峰. 基于情境感知技术的移动数据自动采集系统设计与实现[J]. 数据分析与知识发现, 2017, 1(5): 82-93. [27] Carrascal J P, Church K.An in-situ study of mobile app & mobile search interactions[C]// Proceedings of the 33rd ACM Conference on Human Factors in Computing Systems. New York: ACM Press, 2015: 2739-2748. [28] 姜大庆, 周勇. 基于全序列比对相似度的用户会话自动谱聚类[J]. 计算机科学, 2012, 39(11): 142-144. [29] Cao X, Cong G, Jensen C S.Mining significant semantic locations from GPS data[J]. Proceedings of the VLDB Endowment, 2010, 3(1-2): 1009-1020. [30] Liu D R, Lai C H, Chen Y T.Document recommendations based on knowledge flows: A hybrid of personalized and group-based approaches[J]. Journal of the American Society for Information Science and Technology, 2012, 63(10): 2100-2117. [31] Chuang S L, Chien L F.A practical web-based approach to generating topic hierarchy for text segments[C]// Proceedings of the Thirteenth ACM International Conference on Information and Knowledge Management. New York: ACM Press, 2004: 127-136. [32] Kekäläinen J, Järvelin K.Using graded relevance assessments in IR evaluation[J]. Journal of the American Society for Information Science and Technology, 2002, 53(13): 1120-1129.