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1.
Information filtering is an area getting more important as we have long been flooded with too much information, where product brokering in e-commerce is a typical example. Systems which can provide personalized product recommendations to their users (often called recommender systems) have gained a lot of interest in recent years. Collaborative filtering is one of the commonly used approaches which normally requires a definition of user similarity measure. In the literature, researchers have proposed different choices for the similarity measure using different approaches, and yet there is no guarantee for optimality. In this paper, we propose the use of machine learning techniques to learn the optimal user similarity measure as well as user rating styles for enhancing recommendation acurracy. Based on a criterion function measuring the overall prediction error, several ratings transformation functions for modeling rating styles together with their learning algorithms are derived. With the help of the formulation and the optimization framework, subjective components in user ratings are removed so that the transformed ratings can then be compared. We have evaluated our proposed methods using the EachMovie dataset and succeeded in obtaining significant improvement in recommendation accuracy when compared with the standard correlation-based algorithm. 相似文献
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“211工程”高校图书馆馆藏资源推荐系统调查探析 总被引：1，自引：1，他引：0
[目的/意义]调研推荐系统在高校图书馆中的应用现状及存在的问题,为增强图书馆对知识信息的智能处理能力提供参考依据。[方法/过程]通过对国内116所"211工程"院校进行网站访查和问卷调查,用定量分析与定性分析相结合等方法,对调查结果进行归类、分类统计和对比分析。[结果/结论]研究发现,受访高校图书馆均提供非个性化推荐服务,63%受访高校提供个性化推荐服务;推荐服务内容丰富、方式多样、形式各异,79%的高校积极寻求与其他平台的合作,拓宽推荐深度和广度。存在的问题包括:图书馆推荐系统个性化程度不高,过于依赖图书管理集成系统所附带的推荐功能,不够系统化、智慧化;推荐系统满意度有待提高,有相当多的用户担心推荐系统会泄露个人隐私。 相似文献
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《Government Information Quarterly》2020,37(1):101413
The increasing use of the Internet for service delivery has paralleled an increase of e-service users' privacy concerns as technology offers ample opportunities for organizations to store, process, and exploit personal data. This may reduce individuals' perceived ability to control their personal information and increase their perceived privacy risk. A systematic understanding of individuals' privacy concerns is important as negative user perceptions are a challenge to service providers' reputation and may hamper service delivery processes as they influence users' trust and willingness to disclose personal information. This study develops and validates a model that examines the effect of organizational privacy assurances on individual privacy concerns, privacy control and risk perceptions, trust beliefs and non-self-disclosure behavior. Drawing on a survey to 547 users of different types of e-services – e-government, e-commerce and social networking – in Rwanda, and working within the framework of exploratory analysis, this study uses partial least square-structural equation modeling to validate the overall model and the proposed hypotheses. The findings show that perceptions of privacy risks and privacy control are antecedents of e-service users' privacy concerns, trust and non-self-disclosure behavior. They further show that the perceived effectiveness of privacy policy and perceived effectiveness of self-regulations influence both perceptions of privacy risks and control and their consequences; users' privacy concerns, trust and non-self-disclosure behavior. The hypotheses are supported differently across the three types of e-services, which means that privacy is specific to context and situation. The study shows that the effect of privacy assurances on trust is different in e-government services than in other services which suggest that trust in e-government may be more complex and different in nature than in other contexts. The findings serve to enhance a theoretical understanding of organizational privacy assurances and individual privacy concerns, trust and self-disclosure behavior. They also have implications for e-service providers and users as well as for regulatory bodies and e-services designers. 相似文献
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推荐系统在数字图书馆的应用：研究与技术现状 总被引：1，自引：0，他引：1
Recommender systems are increasingly a necessity as the burden of overly abundant information becomes heavier. This paper examines the current studies on recommender systems in technological perspective as well as the potential use of recommender systems for digital library services and the issues which arise in using recommender systems for library services. 相似文献
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[目的/意义]推荐系统已经成为电子商务网站的重要组成部分之一,为用户提供多种形式的信息推荐服务。国内以淘宝、京东和亚马逊为代表的电子商务网站的推荐系统采用不同的技术架构和多种热点推荐技术,并且越来越重视信息服务的质量。对推荐系统服务质量进行比较研究,能够进一步推动电子商务推荐系统的发展。[方法/过程]首先,从准确性、时效性、新颖性三个技术指标对比以上推荐系统的技术架构对于推荐服务质量的影响;其次,以用户体验作为信息服务质量评价的基础,对182名受访者进行热点技术的认可度调查,研究热点技术对推荐服务质量的影响;最后,对功能模块的用户体验情况进行调查和比较分析。[结果/结论]在这些研究、调查和分析的基础上,给出电子商务推荐系统使用的技术架构和热点技术,以及改进功能模块设计的对策,以进一步提升推荐系统的信息服务质量。 相似文献
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There is an increasing consensus in the Recommender Systems community that the dominant error-based evaluation metrics are insufficient, and mostly inadequate, to properly assess the practical effectiveness of recommendations. Seeking to evaluate recommendation rankings—which largely determine the effective accuracy in matching user needs—rather than predicted rating values, Information Retrieval metrics have started to be applied for the evaluation of recommender systems. In this paper we analyse the main issues and potential divergences in the application of Information Retrieval methodologies to recommender system evaluation, and provide a systematic characterisation of experimental design alternatives for this adaptation. We lay out an experimental configuration framework upon which we identify and analyse specific statistical biases arising in the adaptation of Information Retrieval metrics to recommendation tasks, namely sparsity and popularity biases. These biases considerably distort the empirical measurements, hindering the interpretation and comparison of results across experiments. We develop a formal characterisation and analysis of the biases upon which we analyse their causes and main factors, as well as their impact on evaluation metrics under different experimental configurations, illustrating the theoretical findings with empirical evidence. We propose two experimental design approaches that effectively neutralise such biases to a large extent. We report experiments validating our proposed experimental variants, and comparing them to alternative approaches and metrics that have been defined in the literature with similar or related purposes. 相似文献
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Grace Burchard 《图书情报工作》2007,51(12):33-33
Recommender systems can be a powerful tool for digital libraries if they implement the systems right to information seekers. While patrons have shown an increased interest in recommender systems, digital libraries ought to offer personalized services and assist users both novice and experienced with more sophisticate information retrieval technologies. By guiding users to timely, accurate, and suitable resources within the library the recommender system could take the place of the reference librarian of the bricks and mortar library to enhance the digital libraries services. 相似文献
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Janet Chan 《Journal of the Medical Library Association》2021,109(3):376
Technology advances in eHealth and mHealth are changing the way that health care consumers and providers communicate, receive and deliver care, and access health information. As electronic health records and smartphones have become ubiquitous in the United States, opportunities and applications for the integration of eHealth and mHealth have increased. In addition to technology advances, the changing health care model is simultaneously adapting to and driving initiatives in digital health care. With these digital initiatives have come challenges, including data overload, security and privacy concerns, deficits in technological and health literacy skills, and sorting through the vast number of choices of digital applications. Navigating this changing landscape can be overwhelming and time consuming for both health care providers and consumers. Librarians are uniquely positioned to assist providers and consumers to break down barriers within the digital health care landscape through data management initiatives, technology and health literacy instruction, and finding and evaluating health information and digital health technologies. 相似文献
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提出一个移动互联网环境下用于个性化信息服务的基于情境历史的移动用户偏好挖掘方法,并构建移动旅游信息推荐原型系统CAMTRS。实验结果显示:该方法能较好地获取移动互联网环境下用户的需求偏好,有助于改进个性化推荐系统的预测效果。 相似文献
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《Government Information Quarterly》2021,38(4):101601
Privacy information transparency is generally considered desirable and should be enabled and upheld. It has gained increasing attention giving the emergence of new information technologies and their affordances for e-governance and governments. This study examines the proposition that privacy information transparency is amiable to mitigating privacy fatigue in e-government. The study identifies the antecedents of privacy information transparency of an e-government website, and its influence on privacy fatigue manifested in emotional exhaustion and cynicism. A survey conducted in Cyprus harnessed user responses, and the data analyzed using a partial least square structural equation analysis method. Findings reveal that; (1) user data collection and data use information aspects of online privacy significantly impact privacy information transparency; and (2) privacy information transparency positively impacts both cynicism behaviour and emotional exhaustion. This study extends the concept of privacy fatigue into e-government and contributes to an empirical evaluation of its relationship with privacy information transparency. 相似文献
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一种敏感信息共享隐私保护框架 总被引：1，自引：0，他引：1
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[目的/意义]社会化媒体信息隐私泄露事件频繁发生，加剧了用户对信息隐私的担忧，用户在使用社会化媒体过程中是否愿意向平台披露个人信息成为推动社会化媒体平台健康发展的关键。[方法/过程]利用隐私计算理论和沟通隐私管理理论为框架，结合隐私关注，构建社会化媒体用户信息披露意愿影响模型。以微信平台为例，通过问卷调查的方式收集样本数据，使用Smart PLS软件对模型合理性进行验证。[结果/结论]研究发现，感知收益、信任、感知信息控制均正向影响信息披露意愿，隐私关注负向影响信息披露意愿；信任负向影响感知风险；感知信息控制负向影响隐私关注；隐私倾向正向影响隐私关注和感知风险。 相似文献
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User queries to the Web tend to have more than one interpretation due to their ambiguity and other characteristics. How to diversify the ranking results to meet users’ various potential information needs has attracted considerable attention recently. This paper is aimed at mining the subtopics of a query either indirectly from the returned results of retrieval systems or directly from the query itself to diversify the search results. For the indirect subtopic mining approach, clustering the retrieval results and summarizing the content of clusters is investigated. In addition, labeling topic categories and concept tags on each returned document is explored. For the direct subtopic mining approach, several external resources, such as Wikipedia, Open Directory Project, search query logs, and the related search services of search engines, are consulted. Furthermore, we propose a diversified retrieval model to rank documents with respect to the mined subtopics for balancing relevance and diversity. Experiments are conducted on the ClueWeb09 dataset with the topics of the TREC09 and TREC10 Web Track diversity tasks. Experimental results show that the proposed subtopic-based diversification algorithm significantly outperforms the state-of-the-art models in the TREC09 and TREC10 Web Track diversity tasks. The best performance our proposed algorithm achieves is α-nDCG@5 0.307, IA-P@5 0.121, and α#-nDCG@5 0.214 on the TREC09, as well as α-nDCG@10 0.421, IA-P@10 0.201, and α#-nDCG@10 0.311 on the TREC10. The results conclude that the subtopic mining technique with the up-to-date users’ search query logs is the most effective way to generate the subtopics of a query, and the proposed subtopic-based diversification algorithm can select the documents covering various subtopics. 相似文献
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《Journal of Informetrics》2007,1(1):35-46
This paper presents a method for assessing the quality of similarity functions. The scenario taken into account is that of approximate data matching, in which it is necessary to determine whether two data instances represent the same real world object. Our method is based on the semi-automatic estimation of optimal threshold values. We propose two methods for performing such estimation. The first method is an algorithm based on a reward function, and the second is a statistical method. Experiments were carried out to validate the techniques proposed. The results show that both methods for threshold estimation produce similar results. The output of such methods was used to design a grading function for similarity functions. This grading function, called discernability, was used to compare a number of similarity functions applied to an experimental data set. 相似文献
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Vreixo Formoso Diego Fernández Fidel Cacheda Victor Carneiro 《Information Retrieval》2013,16(6):680-696
Collaborative filtering is a popular recommendation technique. Although researchers have focused on the accuracy of the recommendations, real applications also need efficient algorithms. An index structure can be used to store the rating matrix and compute recommendations very fast. In this paper we study how compression techniques can reduce the size of this index structure and, at the same time, speed up recommendations. We show how coding techniques commonly used in Information Retrieval can be effectively applied to collaborative filtering, reducing the matrix size up to 75 %, and almost doubling the recommendation speed. Additionally, we propose a novel identifier reassignment technique, that achieves high compression rates, reducing by 40 % the size of an already compressed matrix. It is a very simple approach based on assigning the smallest identifiers to the items and users with the highest number of ratings, and it can be efficiently computed using a two pass indexing. The usage of the proposed compression techniques can significantly reduce the storage and time costs of recommender systems, which are two important factors in many real applications. 相似文献
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基于协同理论的企业信息系统集成框架 总被引：1，自引：0，他引：1
协同理论有两层含义:企业内部资源协同,企业外部资源协同即供应链的协同。以协同理论和信息系统的集成方法为依托,提出制造业企业信息系统集成的框架。框架基于数据挖掘技术和Web Services技术,内部协同框架表现为企业应用集成,外部协同框架表现为协同商务平台。整个框架提高了企业内外部信息传递和沟通的有效性,保证了供应链上各个环节信息的有效收集和传递,实现了企业价值增值。图2。参考文献7。 相似文献