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作 者:Gang HUANG Fuqi LIN Yun MA Haoyu WANG Qingxiang WANG Gareth TYSON Xuanzhe LIU
机构地区:[1]Key Lab of High Confidence Software Technologies(Peking University),Ministry of Education,Beijing 100871,China [2]School of Computer Science,Peking University,Beijing 100871,China [3]Institute for Artificial Intelligence,Peking University,Beijing 100871,China [4]School of Cyber Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China [5]Alibaba Group,Beijing 100029,China [6]Hong Kong University of Science and Technology(Guangzhou),Guangzhou 511458,China
出 处:《Science China(Information Sciences)》2025年第4期280-295,共16页中国科学(信息科学)(英文版)
基 金:supported in part by National Natural Science Foundation of China(Grant Nos.62325201,62102009);Beijing Outstanding Young Scientist Program(Grant No.BJJWZYJH01201910001004);Center for Data Space Technology and System,Peking University;supported in part by National Natural Science Foundation of China(Grant No.62072046)。
摘 要:Mobile apps have become widely adopted in our daily lives.To facilitate app discovery,most app markets provide recommendations for users,which may significantly impact how apps are accessed.However,little has been known about the underlying relationships and how they reflect(or affect)user behaviors.To fill this gap,we characterize the app recommendation relationships in the i OS app store from the perspective of the complex network.We collect a dataset containing over 1.3 million apps and 50 million app recommendations.This dataset enables us to construct a complex network that captures app recommendation relationships.Through this,we explore the recommendation relationships between mobile apps and how these relationships reflect or affect user behavior patterns.The insights gained from our research can be valuable for understanding typical user behaviors and identifying potential policy-violating apps.
关 键 词:mobile app RECOMMENDATION complex network user behavior policy-violating app
分 类 号:TP393.092[自动化与计算机技术—计算机应用技术]
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