基于用户信息需求的元搜索引擎的构建

针对当前网络搜索引擎未能较多地关注用户需求、查全率与查准率不高、彼此间不兼容的缺陷,提出建立基于用户需求的元搜索引擎,并分析其基本原理,给出其基本结构,讨论其运行机制和关键技术。指出基于用户需求的元搜索引擎可使网络信息资源在一定程度上结构化,实现网络信息资源的自组织,提高网络信息检索的查全率和查准率.     

宝山社区图书馆协作网发展初探

论文对宝山社区图书馆协作网的发展现状进行了分析和探讨。该协作网是以互联网为依托、以图书配送为手段的新型图书馆模式，创办2年来已成功组建起由区图书馆、乡镇街道图书馆和小区分馆构成的覆盖全区的资源共建共享服务体系。     

访问国内外学术网站数据流量费的解决办法

教学科研需要检索和下载国内外学术站点的学术文献,我国现阶段网络通讯的收费政策与读者需要支付网络流量费是一对矛盾.文章通过分析学术网站访问需求与支付流量费的实际,介绍中国科学技术大学图书馆与网络中心解决流量费问题的方法和实践,以及取得的效果.     

Technological capital: an alternative to the digital divide

This paper identifies individuals’ accumulated history with Information and Communication Technologies (ICTs) as a replacement for the contested and outdated term ‘digital divide.’ We propose that an individual’s ability to benefit from their technological history consists of four factors: awareness, knowledge, access, and technological capacity of the user’s social collective. Together, these factors make up the individual’s level or amount of Technological Capital. The development of this construct was based on empirical research conducted in Soweto, South Africa, and through an analysis of the literature on assessing individuals’ accumulated histories. The concept of technological capital has the potential for application in fields in which ICTs are used for communication, capacity building, and identifying barriers to adoption of new technologies. The use of the concept may have implications for policy decisions, resource allocation, and future research into differences among individuals’ and communities’ ability to benefit from the introduction of new technologies.     

基于自引网络和主路径分析的论文主题创新实证研究

[目的/意义]探讨如何从大量论文中快速发现相关论文,研究论文主题创新的方法,为研究者阅读和利用期刊论文提供参考。[方法/过程]在对论文主题创新和自引网络概念界定的基础上,提出研究论文主题创新的思路、方法和工具。以美国印第安纳大学在图书情报学领域的论文为例进行实证研究。[结果/结论]利用主路径分析可以快速从自引网络中发现由于引用而产生联系的论文,在此基础上可以进行主题创新分析。     

网络舆情场中信息受众观点测度的机理及路径分析

[目的/意义]整合定性与定量的舆情研究视角,统一多模态研究对象,实现网络舆情信息受众的观点测度,可修复网络舆情分析与治理的理论与实践裂痕。[方法/过程]通过引入网络舆情场的概念,对网络舆情信息受众、受众观点测度的内涵进行诠释,就网络舆情场与信息受众观点测度的逻辑关系加以辩证讨论。[结果/结论]提出网络舆情场内舆情受众观点测度机理和具体测度路径,为后续网络舆情场中的网络舆情信息分析、多维度信息受众观点测度,受众认知规律发现,网络舆情监督和管控限制等层面的研究做相应铺垫。     

基于频度演化的领域知识关联关系涌现

领域知识的生长演化问题一直是图书情报学界重点关注的主题。以网络科学思维探索知识生长过程中的关联关系涌现问题,能够对知识关联的生长模式与机制进行揭示。本研究提取知识关联关系累计44万余对,关联频度87万余次,共划分为11个时间窗口。在对时间序列领域知识网络结构属性初步判识的基础上,对关联频度分布进行时间序列分析。并从领域知识生长过程中的关联频度数量、关联频度占比、邻近窗口状态等方面,对知识关联关系及其频度进行跟踪与分析。研究结果表明,知识关联关系生长过程中,关联关系频度的分布符合幂律分布,且在领域知识发展的成熟期表现得更好。知识关联关系的生长过程具有频度层面的“富者更富”的属性,且主要遵循“择优强化”机制。尽管研究所使用的基于社会化标注系统的知识网络尚不足以囊括所有类型的知识网络,但是基于频度演化的知识关联关系涌现模式与机制,有助于促进知识网络、知识生长等领域的研究工作,对于社交网络、传播网络、交通网络等研究不无裨益。图5。表4。参考文献30。     

基于语料库和网络支撑平台的大学英语自主学习：背景、模式与省思

基于语料和数据驱动的大学英语在线学习给传统的教学模式带来了巨大的冲击。文章探讨了该体系的现实和理论背景依托,运作模式及其在践行中所面临的困境和问题进行了理性反思,以期对大学英语教学改革提供新的思路和视角。     

“自媒体”时代高校青年网络行为与引导策略研究

随着互联网技术的发展,微博、掘客等自媒体的使用,改变了媒体的传播格局。"自媒体"时代的来临,使青年学子被其信息形态的多元化、发布平台个性化等特点吸引,成为"自媒体"的最多使用群体,如何将"自媒体"为我所用,提高思政教育的实效性,成为了思政教育者需要面对的问题,本文就是在此现实基础上,进行了问卷调查分析了高校青年网络行为,并提出了引导策略。     

Questioner or question: Predicting the response rate in social question and answering on Sina Weibo

With the noted popularity of social networking sites, people increasingly rely on these social networks to address their information needs. Although social question and answering is potentially an important venue seeking information online, it, unfortunately, suffers from a problem of low response rate, with the majority of questions receiving no response. To understand why the response rate of social question and answering is low and hopefully to increase it in the future, this research analyzes extrinsic factors that may influence the response probability of questions posted on Sina Weibo. We propose 17 influential factors from 2 different perspectives: the content of the question, and the characteristics of the questioner. We also train a prediction model to forecast a question's likelihood of being responded based on the proposed features We test our predictive model on more than 60,000 real-world questions posted on Weibo, which generate more than 600,000 responses. Findings show that a Weibo's question answerability is primarily contingent on the questioner versus the question. Our findings indicate that using appreciation emojis can increase a question's response probability, whereas the use of hashtags negatively influences the chances of receiving answers. Our contribution is in providing insights for the design and development of future social question and answering tools, as well as for enhancing social network users’ collaboration in supporting social information seeking activities.