While recommendation plays an increasingly critical role in our living, study, work, and entertainment, the recommendations we receive are often for irrelevant, duplicate, or uninteresting products and ser- vices. A c...While recommendation plays an increasingly critical role in our living, study, work, and entertainment, the recommendations we receive are often for irrelevant, duplicate, or uninteresting products and ser- vices. A critical reason for such bad recommendations lies in the intrinsic assumption that recommend- ed users and items are independent and identically distributed （liD） in existing theories and systems. Another phenomenon is that, while tremendous efforts have been made to model specific aspects of users or items, the overall user and item characteristics and their non-IIDness have been overlooked. In this paper, the non-liD nature and characteristics of recommendation are discussed, followed by the non-liD theoretical framework in order to build a deep and comprehensive understanding of the in- trinsic nature of recommendation problems, from the perspective of both couplings and heterogeneity. This non-liD recommendation research triggers the paradigm shift from lid to non-liD recommendation research and can hopefully deliver informed, relevant, personalized, and actionable recommendations. It creates exciting new directions and fundamental solutions to address various complexities including cold-start, sparse data-based, cross-domain, group-based, and shilling attack-related issues.展开更多
Standard e-government information system(SEIS) including mobile-government applications are playing more and more important roles in the establishing of national e-government framework. It can be beneficial not only f...Standard e-government information system(SEIS) including mobile-government applications are playing more and more important roles in the establishing of national e-government framework. It can be beneficial not only for avoiding redundant e-government IS development but also for improving collaboration among government agencies. Two research questions were explored: what are the factors influencing the performance of SEIS? Will mandatory SEIS create a better performance than non-mandatory SEIS? Specifically, the use of five categories of IS aspects--information system quality, online service quality, offline service quality, diffusion modes and standard network size—is proposed to understand the performance of SEIS through applying both survey study and simulation study. The results show that information system quality and online service quality of SEIS have strong effects on users' expectation and users' satisfaction, which thereafter promotes the performance of SEIS. Government agencies' offline service quality shows a significant effect on users' satisfaction while not on users' expectation. Furthermore, the diffusion speed of SEIS in non-mandatory and mandatory modes and the standard network size also have great influence on the utility of SEIS.展开更多
文摘While recommendation plays an increasingly critical role in our living, study, work, and entertainment, the recommendations we receive are often for irrelevant, duplicate, or uninteresting products and ser- vices. A critical reason for such bad recommendations lies in the intrinsic assumption that recommend- ed users and items are independent and identically distributed （liD） in existing theories and systems. Another phenomenon is that, while tremendous efforts have been made to model specific aspects of users or items, the overall user and item characteristics and their non-IIDness have been overlooked. In this paper, the non-liD nature and characteristics of recommendation are discussed, followed by the non-liD theoretical framework in order to build a deep and comprehensive understanding of the in- trinsic nature of recommendation problems, from the perspective of both couplings and heterogeneity. This non-liD recommendation research triggers the paradigm shift from lid to non-liD recommendation research and can hopefully deliver informed, relevant, personalized, and actionable recommendations. It creates exciting new directions and fundamental solutions to address various complexities including cold-start, sparse data-based, cross-domain, group-based, and shilling attack-related issues.
基金supported by the Natural Science Foundation of China (71103021, 71573022, 71372193, 71301106)Beijing Philosophy and Social Science Planning Foundation (13JGC085)+1 种基金Beijing Higher Education Yong Elite Teacher Foundation (YETP0852)Humanities and Social Sciences Foundation of the Ministry of Education(13YJC630034, 13YJA790023)
文摘Standard e-government information system(SEIS) including mobile-government applications are playing more and more important roles in the establishing of national e-government framework. It can be beneficial not only for avoiding redundant e-government IS development but also for improving collaboration among government agencies. Two research questions were explored: what are the factors influencing the performance of SEIS? Will mandatory SEIS create a better performance than non-mandatory SEIS? Specifically, the use of five categories of IS aspects--information system quality, online service quality, offline service quality, diffusion modes and standard network size—is proposed to understand the performance of SEIS through applying both survey study and simulation study. The results show that information system quality and online service quality of SEIS have strong effects on users' expectation and users' satisfaction, which thereafter promotes the performance of SEIS. Government agencies' offline service quality shows a significant effect on users' satisfaction while not on users' expectation. Furthermore, the diffusion speed of SEIS in non-mandatory and mandatory modes and the standard network size also have great influence on the utility of SEIS.
