数据管理能力成熟度模型比较研究与启示     

叶兰 《图书情报工作》2020,64(13):51-57

[目的/意义] 对比分析数据管理能力成熟度模型，为图书馆选择与应用数据管理能力成熟度模型提供参考方案。[方法/过程] 通过模型文本的研究，介绍各模型的结构。采用比较分析法从评价维度（功能域）的设置、模型的组织体系、评价标准与规则、可操作性、公开度等5个方面对7个数据管理能力成熟度模型进行评析。[结果/结论] 每个模型具有其特色功能。CMMI、DMM、DCAM和中国DCMM的评价维度较为全面，中国DCMM即中国-数据中心服务能力成熟度模型具有较强的操作性，且其定量与定性相结合的评价方法值得借鉴。研究数据管理的能力成熟度模型（雪城大学秦健教授团队）和研究数据管理能力成熟度模型（澳大利亚ANDS）考虑图书馆数据管理的实际情况，可作为首选模型。基于各模型的对比与评析结果，形成3种适应不同情境的图书馆选择与应用数据管理能力成熟度模型的方案。  相似文献   

灰色预测法在情报研究中的应用研究综述     

张晶晶  李泽霞 《图书情报工作》2020,64(24):106-114

[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据，通过对灰色预测法在情报研究中的应用情况进行梳理，总结其在应用过程中存在的不足，为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献，从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述，总结当前情报研究中灰色预测法的应用所存在的问题，并提出改进建议。[结果/结论] 在方法应用上，已有研究主要采用数列灰预测，且模型集中在单变量灰色预测模型，根据预测对象不同，灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用，未来可根据预测对象特点及研究目标尝试不同的灰色预测方法，扩宽灰色预测法在其他方面的情报研究问题中的应用。  相似文献   

Audience management,online turbulence and lurking in social networking services: A transactional process of stress perspective     

《International Journal of Information Management》2021

In social networking services (SNSs), users’ unclear understanding of the large and invisible audience increases the chances of online turbulence, which is a key source of SNS-induced stress. This growing phenomenon has gained increasing attention in academia and industry due to the undesirable consequences for users and SNS platforms. In this study, we draw from the transactional model of stress to examine how audience management strategies impact online turbulence and lead to neglected unintended audience concern and lurking. We also investigate the role of self-monitoring as a stress inhibitor. We test our model with data collected from 301 SNS users. The results show that the four types of audience management strategies have different effects on online turbulence, which significantly impacts neglected unintended audience concern especially when users have high self-monitoring skills. We believe that this work contributes, both from scientific and practical standpoints, to the understanding of the interventions and stressful responses of online turbulence in SNSs.  相似文献   

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws     

Edgardo Ferretti  Leticia Cagnina  Viviana Paiz  Sebastián Delle Donne  Rodrigo Zacagnini  Marcelo Errecalde 《Information processing & management》2018,54(6):1169-1181

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献   

Tracking user-role evolution via topic modeling in community question answering     

Chaogang Fu 《Information processing & management》2019,56(6):102075

Community question answering (CQA) services that enable users to ask and answer questions are popular on the internet. Each user can simultaneously play the roles of asker and answerer. Some work has aimed to model the roles of users for potential applications in CQA. However, the dynamic characteristics of user roles have not been addressed. User roles vary over time. This paper explores user representation by tracking user-role evolution, which could enable several potential applications in CQA, such as question recommendation. We believe this paper is the first to track user-role evolution and investigate its influence on the performance of question recommendation in CQA. Moreover, we propose a time-aware role model (TRM) to effectively track user-role evolution. With different independence assumptions, two variants of TRM are developed. Finally, we present the TRM-based approach to question recommendation, which provides a mechanism to naturally integrate the user-role evolution with content relevance between the answerer and the question into a unified probabilistic framework. Experiments using real-world data from Stack Overflow show that (1) the TRM is valid for tracking user-role evolution, and (2) compared with baselines utilizing role based methods, our TRM-based approach consistently and significantly improves the performance of question recommendation. Hence, our approach could enable several potential applications in CQA.  相似文献   

学习团队协作信息搜索的共享心智模型研究   总被引：1，自引：0，他引：1  

颜端武  张馨月  汤佳丽  苏琼 《图书情报工作》2020,64(8):3-12

[目的/意义] 对协作信息搜索进行深入研究，为专业化协作信息搜索系统平台建设优化等提供启发和借鉴。[方法/过程] 聚焦于学习团队的信息搜索行为，以高校学生为研究样本，以共享心智模型为切入点，采用扎根理论研究方法，探讨协作信息搜索中团队共享心智模型建构过程。[结果/结论] 识别出四大核心环节——个体感知与探索、团队任务解析、团队信息收集和团队信息整合，并理清各环节的认知活动与共享心智模型内容要素。  相似文献   

基于二模复杂网络的隐性知识发现方法研究——以潜在药物靶点挖掘为例     

李东巧  陈芳  韩涛  杨艳萍  王学昭  王燕鹏  Cynthia Liu  Yingzhu Li 《图书情报工作》2020,64(21):120-129

[目的/意义] 通过构建二模复杂网络模型，揭示隐藏在海量文献中的隐性知识。[方法/过程] 通过NetworkX复杂网络工具包，依据任意两个节点的共现关系构建二模复杂网络模型；对网络模型中节点的共现关系进行加权，计算网络的拓扑信息并进行AP聚类，提取节点间的直接关系；采用AUC方法对AA、JC、加权改进的wAA和wJC等4种链路预测算法进行评价，遴选出最合适的预测算法，并对复杂网络的隐性关系进行预测分析。[结果/结论] 以潜在药物靶点挖掘为例进行的实证研究结果表明，wAA链路预测算法为最优的链路预测算法；二模复杂网络模型、指标和方法体系在美国化学文摘社数据库中的药物靶点挖掘中具有一定的有效性。下一步计划在其他数据库中或其他研究领域中进行尝试，以进一步验证该模型的通用性和有效性。  相似文献   

政府数据开放中的公众参与模式:理论构建与案例实证     

陈朝兵  简婷婷 《图书情报工作》2020,64(22):58-68

[目的/意义] 探讨政府数据开放中公众参与的理论模式，旨在指导政府部门有效实现公众参与数据开放的政策目标，以及推进政府数据开放中公众参与议题的研究进展。[方法/过程] 采用文献分析法、逻辑分析法和案例分析法，同时以公众参与阶梯理论作为分析工具，构建并实证政府数据开放中的公众参与模式。[结果/结论] 政府数据开放中的公众参与可从理论层面构建为告知型参与、咨询型参与、合作型参与和授权型参与4种模式，其核心涵义分别是政府向公众传达信息、政府咨询公众意见、政府与公众平等合作、政府与公众共同治理。这4种政府数据开放公众参与理论模式一方面在政府意图、主导力量、信息流动、公众信息知晓度和公众自治程度方面存在明显的特征差异，另一方面从国内外政府数据开放公众参与实践案例中获得良好的经验支持。  相似文献   

区域协同发展战略下京津冀体育产业一体化发展研究     

李艳荣  张长念 《广州体育学院学报》2019,(1):40-44

推动京津冀体育产业一体化发展，既是推进京津冀协同发展的重要内涵，也是体育领域落实区域协调发展战略的具体实践。研究表明，京津冀体育产业一体化发展，既面临难得的历史机遇，也面临着严峻的挑战。挑战在于：整体发展失衡，结构亟待优化；市场发育不足，行业竞争加剧；资源环境恶化，低碳锁定障碍；顶层设计不足，合作机制缺失。基于区域协调发展战略，应优化空间布局，推动体育产业错位发展；培育消费市场，推动体育产业创新发展；加快转型升级，推动体育产业低碳发展；完善合作机制，推动体育产业协同发展。  相似文献   

Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods     

《International Journal of Information Management》2019

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).  相似文献