基于時(shí)空感知的用戶角色推理
doi: 10.11999/JEIT150700 cstr: 32379.14.JEIT150700
-
2.
(武漢大學(xué)計(jì)算機(jī)學(xué)院 武漢 430079) ②(空軍預(yù)警學(xué)院 武漢 430019)
基金項(xiàng)目:
國家自然科學(xué)基金(61272109)，中央高?；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金(2042014kf0057)，湖北省自然科學(xué)基金(2014CFB289)，空軍預(yù)警學(xué)院青年創(chuàng)新基金(2013ZDJC0101)
Inferring Social Roles with Spatio-temporal Awareness
-
2.
(Computer School, Wuhan University, Wuhan 430079, China)
Funds:
The National Natural Science Foundation of China (61272109), The Fundamental Research Funds for Central Universities (2042014kf0057), The National Natural Science Foundation of Hubei Province of China (2014CFB289), Air Force Early Warning Academy (2013ZDJC0101)
-
摘要: 隨著大數(shù)據(jù)和信息技術(shù)的發(fā)展，更好地理解用戶的行為軌跡在個(gè)性化推薦、廣告推薦等方面越來越重要。該文依據(jù)大數(shù)據(jù)環(huán)境下的城市計(jì)算理論，提出一種基于情境感知的用戶角色推理模型。通過用戶的行為軌跡分析其行為的時(shí)空特性；結(jié)合時(shí)間、語義分析等構(gòu)造識別用戶角色概率推理模型；通過算法克服識別用戶角色的主觀性、動態(tài)適應(yīng)性差等問題。實(shí)驗(yàn)結(jié)果證明了該文所提模型的可行性、精確性和預(yù)測準(zhǔn)確性。
-
關(guān)鍵詞:
- 大數(shù)據(jù) /
- 城市計(jì)算 /
- 情境感知 /
- 用戶角色
Abstract: With the development of big data and information technology, a better understanding of users trajectories is of great importance for the design of many applications, such as personalized recommendation, behavioral targeting and computational advertising. In this paper, with the theory of urban computing based on big data, a model of recognizing information veracity of users on the social media networks is proposed. The behavior characteristics of users trajectories based on context awareness are analyzed. The model of recognizing the truth of social roles is formalized and built. The subjectivity of recognizing users roles is overcomed. Furthermore, experiments are conducted with large-scale and real-world datasets. The results show that the proposed model offers a powerful ability for recognition of truth social roles.-
Key words:
- Big data /
- Urban computing /
- Context awareness /
- Social roles
-
王靜遠(yuǎn), 李超, 熊璋, 等. 以數(shù)據(jù)為中心的智慧城市研究綜述[J]. 計(jì)算機(jī)研究與發(fā)展, 2014, 51(2): 239-259. WANG Jingyuan, LI Chao, XIONG Zhang, et al. Survey of data-centric smart city[J]. Journal of Computer Research and Development, 2014, 51(2): 239-259. 李鵬, 于曉洋, 孫渤禹, 等. 基于用戶群組行為分析的視頻推薦方法研究[J]. 電子與信息學(xué)報(bào), 2014, 36(6): 1485-1491. doi: 10.3724/SP.J.1146.2013.01225. LI Peng, YU Xiaoyang, SUN Boyu, et al. Video recommendation method based on group user behavior analysis[J]. Journal of Electronics Information Technology, 2014, 36(6): 1485-1491. doi: 10.3724/SP.J.1146.2013.01225. 徐風(fēng)苓, 孟祥武, 王立才. 基于移動用戶上下文相似度的協(xié)同過濾推薦算法[J]. 電子與信息學(xué)報(bào), 2011, 33(11): 2785-2789. doi: 10.3724/SP.J.1146.2011.00384. XU Fengling, MENG Xiangwu, and WANG Licai. A collaborative filtering recommendation algorithm based on context similarity for mobile users[J]. Journal of Electronics Information Technology, 2011, 33(11): 2785-2789. doi: 10.3724/SP.J.1146.2011.00384. PAN Gang, QI Guande, ZHANG Wangsheng, et al. Trace analysis and mining for smart cities: Issues, methods, and applications[J]. IEEE Communications Magazine, 2013, 51(6): 120-126. 王玉斌, 孟祥武, 胡勛. 一種基于信息老化的協(xié)同過濾推薦算法[J]. 電子與信息學(xué)報(bào), 2013, 35(10): 2391-2396. doi: 10.3724/SP.J.1146.2012.01473. WANG Yubin, MENG Xiangwu, and HU Xun. Information aging-based collaborative filtering recommendation algorithm[J]. Journal of Electronics Information Technology, 2013, 35(10): 2391-2396. doi: 10.3724/SP.J.1146. 2012.01473. YAN Zhixian, CHAKRABOTRY D, PARENT C, et al. Semantic trajectories: Mobility data computation and annotation[J]. ACM Transactions on Intelligent Systems and Technology, 2012, 9(4): 39: 1-39: 34. YING J J C, LEE W C, and TSENG V S. Mining geographic-temporal-semantic patterns in trajectories for location prediction[J]. ACM Transactions on Intelligent Systems and Technology, 2013, 5(1): 2:1-2:34. HENDERSON K, GALLAGHER B, ELIASSI-RAD T, et al. RolX: Structural role extraction mining in large graphs[C]. Proceeding of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, 2012: 1231-1239. 馬宇馳, 楊寧, 謝琳, 等. 基于軌跡時(shí)空關(guān)聯(lián)語義和時(shí)態(tài)熵的移動對象社會角色發(fā)現(xiàn)[J]. 計(jì)算機(jī)研究與發(fā)展, 2012, 49(10): 2153-2160. MA Yuchi, YANG Ning, XIE Lin, et al. Social roles discovery of moving objects based on spatial temporal associated semantics and temporal entropy of trajectories[J]. Journal of Computer Research and Development, 2012, 49(10): 2153-2160. MCPHERSON M, SMITH-LOVIN L, and COOK J M. Birds of a feather: homophily in social networks [J]. Annual Review of Sociology, 2001(27): 415-444. MISLOVE A, VISWANATH B, KRISHNA P G, et al. You are who you know: Inferring user profiles in online social networks[C]. Proceedings of the 3rd International Conference on Web Search and Web Data Mining, New York, 2010: 251-260. TAN Chenhao, LEE Lililan, TANG Jie, et al.. User-level sentiment analysis incorporating social networks[C]. Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, 2011: 1397-1405. TANG J, LOU T, and KLEINBERG J. Inferring social ties across heterogeneous networks[C]. Proceedings of the 5th International Conference on Web Search and Web Data Mining, Seattle, 2012: 743-752. ZHAO Yuchen, WANG Guan, YU Philip S, et al. Inferring social roles and statuses in social networks[C]. Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, 2013: 695-703. YUAN Jing, ZHENG Yu, and XIE Xing. Discovering regions of different functions in a city using human mobility and pois[C]. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Beijing, 2012: 186-194. YUAN Jing, ZHENG Yu, XIE Xing, et al. Discovering urban functional zones using latent activity trajectories[J]. IEEE Transactions on Knowledge and Data Engineering, 2015, 27(3): 712-725. CHO E, MYERS S A, and LESKOVEC J. Friendship and mobility: User movement in location-based social networks[C]. Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, 2011: 1082-1090. 馬武彬, 劉明星, 黃宏斌, 等. 依據(jù)歷史軌跡構(gòu)建城市出租車移動概率模型[J]. 國防科技大學(xué)學(xué)報(bào), 2014, 36(6): 129-134. MA Wubin, LIU Mingxing, HUANG Hongbin, et al. The moving probability model of urban cabs based on history trajectory[J]. Journal of National University of Defense Technology, 2014, 36(6): 129-134. YING Jiaching, LU Chan, LEE Wangchien, et al. Mining user similarity from semantic trajectories[C]. Proceedings of the 2010 International Workshop on Location Based Social Networks, San Jose, 2010: 19-26 -
計(jì)量
- 文章訪問數(shù): 1357
- HTML全文瀏覽量: 148
- PDF下載量: 691
- 被引次數(shù): 0
下載:
