现代信息技术背景下普通高校课外体育活动创新研究     

管月泉  陈欣 《当代体育科技》2020,(11):120-121

随着现代信息技术的快速发展,"互联网+"这一概念频繁出现在公众视野。同时,,对高校体育事业的发展也产生了不可估量的影响。在《体育发展"十三五"规划》中,再次表明要实施"互联网+体育"战略,要将"互联网+"与全民运动融合到一起。本文在简要分析高校大学生课外体育活动现状基础上,重点探讨了基于手机APP创新普通高校课外体育活动的具体建议。  相似文献   

个性服务视域下的高校档案数据库建设     

沙敏 《档案管理》2020,(3):115-116

本文通过研究当前高校档案管理的重要性,结合实际的档案需求情况,分析了档案专题数据库基本的几种类型,来满足高校群体对档案信息的个性化需求,并通过对档案专题数据库模式的分析,制定了具体的应用措施,以便能够为相关人员提供信息参考。  相似文献   

数字图书馆信息服务的融合与创新——基于2019年JCDL年会论文的综述     

梁少博  吴丹 《图书情报知识》2020,(3):97-108

[目的/意义]本文通过对2019年国际数字图书馆联合会议(Joint Conference on Digital Library,JCDL)的录用论文进行整体回顾,梳理了本届年会的最新研究成果与学科发展动态,以助国内图情领域学者更好地了解本届年会成果,把握国际数字图书馆领域研究的前沿热点问题。[研究设计/方法]采用文献综述的方法进行研究。[结论/发现]本届年会更加关注数字图书馆如何通过多源数据的融合、数字人文馆藏资源的利用等实现信息服务深度融合;数字图书馆如何通过海量大数据挖掘与利用、用户行为分析提升其服务水平;如何通过对学术文本资源深入挖掘,实现信息计量学在学术评审、学术评价等方面的创新应用。[创新/价值]本文揭示了国际数字图书馆领域的最新发展态势,展望了未来数字图书馆领域的学术前沿方向。  相似文献   

RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification     

《Information processing & management》2023,60(2):103235

Imbalanced sample distribution is usually the main reason for the performance degradation of machine learning algorithms. Based on this, this study proposes a hybrid framework (RGAN-EL) combining generative adversarial networks and ensemble learning method to improve the classification performance of imbalanced data. Firstly, we propose a training sample selection strategy based on roulette wheel selection method to make GAN pay more attention to the class overlapping area when fitting the sample distribution. Secondly, we design two kinds of generator training loss, and propose a noise sample filtering method to improve the quality of generated samples. Then, minority class samples are oversampled using the improved RGAN to obtain a balanced training sample set. Finally, combined with the ensemble learning strategy, the final training and prediction are carried out. We conducted experiments on 41 real imbalanced data sets using two evaluation indexes: F1-score and AUC. Specifically, we compare RGAN-EL with six typical ensemble learning; RGAN is compared with three typical GAN models. The experimental results show that RGAN-EL is significantly better than the other six ensemble learning methods, and RGAN is greatly improved compared with three classical GAN models.  相似文献   

Platform-based customer agility: An integrated framework of information management structure,capability, and culture     

《International Journal of Information Management》2021

Platform-based customer agility is the ability to leverage the voice of the customer on a platform to achieve market intelligence and to explore competitive action opportunities. Prior studies have indicated the critical role of customer agility in enabling the survival and prosperity of contemporary organizations in a turbulent business environment, although how to develop this capability is not answered. The current research attempts to fill this theoretical gap. Drawing on the information management literature, we propose an integrative information management framework to investigate the process of developing customer agility. By conducting a case study of a leading e-commerce platform in China, we identify three types of platform-based customer agility (i.e. reactive customer agility, proactive customer agility, and coactive customer agility) in different phases of the growth of the platform. Furthermore, a process model is developed from the case study. It shows that platform-based customer agility is achieved by establishing information management structure, developing information management capability, and instilling information management culture. This study contributes to the knowledge on customer agility and information management. Detailed recommendations are also provided for potential practitioners.  相似文献   

The effect of toxicity on COVID-19 news network formation in political subcommunities on Reddit: An affiliation network approach     

《International Journal of Information Management》2021

Political polarization remains perhaps the “greatest barrier” to effective COVID-19 pandemic mitigation measures in the United States. Social media has been implicated in fueling this polarization. In this paper, we uncover the network of COVID-19 related news sources shared to 30 politically biased and 2 neutral subcommunities on Reddit. We find, using exponential random graph modeling, that news sources associated with highly toxic – “rude, disrespectful” – content are more likely to be shared across political subreddits. We also find homophily according to toxicity levels in the network of online news sources. Our findings suggest that news sources associated with high toxicity are rewarded with prominent positions in the resultant network. The toxicity in COVID-19 discussions may fuel political polarization by denigrating ideological opponents and politicizing responses to the COVID-19 pandemic, all to the detriment of mitigation measures. Public health practitioners should monitor toxicity in public online discussions to familiarize themselves with emerging political arguments that threaten adherence to public health crises management. We also recommend, based on our findings, that social media platforms algorithmically promote neutral and scientific news sources to reduce toxic discussion in subcommunities and encourage compliance with public health recommendations in the fight against COVID-19.  相似文献   

Information resource orchestration during the COVID-19 pandemic: A study of community lockdowns in China     

《International Journal of Information Management》2020

The outbreak of the COVID-19 pandemic has created significant challenges for people worldwide. To combat the virus, one of the most dramatic measures was the lockdown of 4 billion people in what is believed to be the largest quasi-quarantine in human history. As a response to the call to study information behavior during a global health crisis, we adopted a resource orchestration perspective to investigate six Chinese families who survived the lockdown. We explored how elderly, young and middle-aged individuals and children resourced information and how they adapted their information behavior to emerging online technologies. Two information resource orchestration practices (information resourcing activities and information behavior adaptation activities) and three mechanisms (online emergence and convergence in community resilience, the overcoming of information flow impediments, and the application of absorptive capacity) were identified in the study.  相似文献   

The Mystery Room: discovering the flexibility of an information literacy-based educational escape room     

Glenn Koelling  Alyssa Russo 《Public Services Quarterly》2020,16(1):1-11

Abstract

The Mystery Room is an educational escape room based on information literacy and applied to multiple audiences, including first-year students and library student employees. In this article, we explain how we developed the game, its theoretical underpinnings, and why it’s a flexible workshop for a variety of audiences.  相似文献   

Web document summarization by exploiting social context with matrix co-factorization     

Minh-Tien Nguyen  Viet Cuong Tran  Xuan Hoai Nguyen  Le-Minh Nguyen 《Information processing & management》2019,56(3):495-515

In the context of social media, users usually post relevant information corresponding to the contents of events mentioned in a Web document. This information posses two important values in that (i) it reflects the content of an event and (ii) it shares hidden topics with sentences in the main document. In this paper, we present a novel model to capture the nature of relationships between document sentences and post information (comments or tweets) in sharing hidden topics for summarization of Web documents by utilizing relevant post information. Unlike previous methods which are usually based on hand-crafted features, our approach ranks document sentences and user posts based on their importance to the topics. The sentence-user-post relation is formulated in a share topic matrix, which presents their mutual reinforcement support. Our proposed matrix co-factorization algorithm computes the score of each document sentence and user post and extracts the top ranked document sentences and comments (or tweets) as a summary. We apply the model to the task of summarization on three datasets in two languages, English and Vietnamese, of social context summarization and also on DUC 2004 (a standard corpus of the traditional summarization task). According to the experimental results, our model significantly outperforms the basic matrix factorization and achieves competitive ROUGE-scores with state-of-the-art methods.  相似文献   

Neural embedding-based indices for semantic search     

Fatemeh Lashkari  Ebrahim Bagheri  Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755

Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus.  相似文献