合作信息查寻与检索中知识共享的博弈学习机制研究

以二人合作为对象,讨论合作信息查寻与检索中知识共享的博弈学习机制,在简化的假设条件下,分别就检索过程共享及检索结果共享构建知识共享的博弈学习模型并求最优解。研究表明:学习是参与者的优选策略,共享在一定激励条件下才能发生;在一定的激励机制或约束条件下,参与者有逐渐走向合作博弈学习的趋势并到达“共享”与“学习”均衡。     

图书情报学高被引论文引用现象的实证研究

学术论文是科研活动产出和知识信息交流的主要载体,而学术论文被引用则是学术成果获得认同的主要方式之一。研究高被引论文所引用论文的分布特征,对于了解高被引论文知识基础的构成具有重要意义。本文以ISI图书情报学（Information Science & Library Science）为例,以实证研究为基础,按比例采集图书情报学领域的高被引论文数据,查询这些高被引论文的参考文献的被引频次数据,以期得到高被引论文的引证特点。研究发现,图书情报学领域的高被引论文更多地引用了高被引参考文献;随着被引频次的降低,其引用的高被引论文所占的比例也在下降。     

SCI、EI收录情况比较分析

在简要介绍两种检索工具的基础上,对近几年SCI、EI收录中文科技期刊的情况进行比较,同时分析某些文章未被其收录的原因。     

“信息素养与信息检索通用教程”慕课及其教材的一体化建设

“信息素养与信息检索通用教程”慕课及其配套教材正在同步建设,其内容体系首次创设了生活、学习、工作三大现实检索场景,采用了人物设定、情境代入、任务驱动、模拟教学四个有趣方式,践行好看、好学、好记、好用、好玩的“五好”理念,将为所有学科和专业的本科生与研究生、信息管理从业人员、以及各行各业和各个领域有意提升信息素养和信息检索能力的社会人士提供全新而优质的学习资源.     

Meta-synthesis in Library & Information Science Research

The meta-synthesis method has received increased interest in social science research, but relatively few meta-synthesis studies have been conducted in the library and information science (LIS) field. The purpose of this study was to analyze 44 LIS-related meta-synthesis studies in terms of contribution, meta-synthesis methodology, and research topics. The results revealed that there are four types of contributions of meta-synthesis research: isolated findings, non-dynamic relationships, dynamic relationships, and models. Moreover, a variety of methods have been used to search, select, analyze, and synthesize the individual studies. Finally, although meta-synthesis studies have been conducted on some LIS topics (e.g., health informatics, library user services, and information management), it has been an undervalued method for other research topics. Recommendations are offered to encourage the use of this method and to guide researchers to conduct more rigorous meta-synthesis studies on LIS topics.     

美国图书馆协会的图书情报学硕士教育认证机制

以网络访问的方式学习了美国图书馆协会的图书情报学专业硕士认证体系,从认证体系的主要内容、特点、影响等方面,介绍、分析其核心竞争力、核心课程及基本要求,归纳出美国图书情报学硕士教育认证体系的基本结构及渗透于其中的教育理念。     

Information Skills for Distance Learning

Abstract

In spring 1997, the Education Services department at the University of North Carolina at Chapel Hill (UNC-CH) Health Sciences Library (HSL) developed six Web-based tutorials designed to teach information skills. This paper describes how the modules were created.     

Automated Epistemology: Bots,Computational Propaganda & Information Literacy Instruction

Computational technologies have vastly replaced our prior modalities of information seeking. Social media platforms have become the first choice of many information seekers. Increasingly, these platforms are also becoming vehicles for coordinated, manipulative disinformation campaigns. These campaigns of computational propaganda have resulted in an information environment in which the assignment of authority and trust in information sources has become increasingly opaque. This epistemic process of information evaluation has increasingly become the purview of automated algorithmic systems that we as human beings tend to falsely implicitly trust to provide us with the most accurate information available. Propagandists have begun to exploit the algorithmic components of these systems as well as human cognitive deficits in order to manipulate public opinion, control the narrative of public discourse, and flood our information ecosystems in order to work towards the manufacture of false consensus on a wide range of political and cultural issues. This work aims to review and synthesize the literature on computational propaganda, how it manipulates our human cognitive deficits, and how information literacy can be utilized in order to correct for the resultant epistemic failure.     

面向技术创新的企业信息情报能力成熟度诊断模型研究

首先对企业技术创新中的信息流动进行分析,发现企业信息流动要经过外部环境监测、评估与辨识、深入获取、分析与加工、传播和应用共6个环节。根据企业信息流动环节归纳出企业信息情报能力由内部信息共享能力、外部信息获取能力、创新信息分析能力和创新信息应用能力等4个维度组成。然后将企业信息情报能力发展阶段划分为混沌、萌芽、发展、成熟4个阶段。根据企业信息情报发展阶段,将企业信息情报能力成熟度诊断模型分为4个级别,混沌阶段对应第一级不规范;萌芽阶段对应第二级有规范;发展阶段对应第三级有效;成熟阶段对应第四级高效。最后,将诊断模型运用到长沙市工业和信息化委员会组织的长沙市中小企业“协同创新”示范活动中,效果良好,验证了企业信息情报能力成熟度诊断模型的有效性。     

基于无监督图神经网络的学术文献表示学习研究

学术文献特征表示,是学术文献搜索、分类组织、个性化推荐等学术大数据服务的关键步骤。研究表明,图神经网络能够有效学习文献的特征表示,然而当前研究主要集中在有监督学习方法上,不仅对数据集的大小和质量的要求较高,且学习到的文献特征表示与具体任务高度耦合。基于此,本文将四种无监督图神经网络方法引入学术文献表示学习,从Cora、CiteSeer和DBLP (database systems and logic programming)数据集的引文网络、共被引网络和文献耦合网络中学习文献的表示向量,并应用于文献分类和论文推荐两大下游任务。研究结果表明,(1)深度互信息图神经网络适合于文献分类任务,对抗正则化变分图自编码器则在论文推荐任务上性能更佳;(2)Cora数据集上的结果表明,相较于共被引和文献耦合网络,引文网络更适合于学习通用的文献表示向量。     

Guided and Team-Based Learning for Chemical Information Literacy

This case study recounts a process of course design, conduct, and evaluation for a single-session chemical information literacy class using guided and team-based learning. This approach incorporates active learning, worked examples, process worksheets, and POGIL elements. The instruction followed an iterative cycle of learning exercises whereby (1) the instructor introduces an information problem or task through a short presentation, (2) student teams collaboratively work through process worksheets that guide them through the technical and analytical tasks of resolving the information problem or task, (3) the instructor serves as a facilitator to address learning needs that arise during the exercise, while student teams analyze and reflect upon the learning activity and concepts, and afterwards, (4) the class engages in a discussion as an opportunity for evaluation, further exploration, and peer instruction. Overall, the guided and team-based learning approach offers opportunities to observe student progress closely and forges a collaborative spirit between students and the instructor for an engaging and rewarding experience.     

合作信息查寻与检索的5C模型与语境机制

基于合作信息查寻与检索理论模型构建的相关研究工作综述发现语境在合作查寻与检索过程中居于重要地位。在详细分析语境内涵并对比相关概念的基础上,指出语境在合作信息查寻与检索研究中具有方法论属性,并提出以语境为基础的合作信息查寻与检索5C模型。基于5C模型探讨合作信息查寻与检索的路径选择,并揭示其语境运行机制。     

Applying Machine Learning to Text Segmentation for Information Retrieval

We propose a self-supervised word segmentation technique for text segmentation in Chinese information retrieval. This method combines the advantages of traditional dictionary based, character based and mutual information based approaches, while overcoming many of their shortcomings. Experiments on TREC data show this method is promising. Our method is completely language independent and unsupervised, which provides a promising avenue for constructing accurate multi-lingual or cross-lingual information retrieval systems that are flexible and adaptive. We find that although the segmentation accuracy of self-supervised segmentation is not as high as some other segmentation methods, it is enough to give good retrieval performance. It is commonly believed that word segmentation accuracy is monotonically related to retrieval performance in Chinese information retrieval. However, for Chinese, we find that the relationship between segmentation and retrieval performance is in fact nonmonotonic; that is, at around 70% word segmentation accuracy an over-segmentation phenomenon begins to occur which leads to a reduction in information retrieval performance. We demonstrate this effect by presenting an empirical investigation of information retrieval on Chinese TREC data, using a wide variety of word segmentation algorithms with word segmentation accuracies ranging from 44% to 95%, including 70% word segmentation accuracy from our self-supervised word-segmentation approach. It appears that the main reason for the drop in retrieval performance is that correct compounds and collocations are preserved by accurate segmenters, while they are broken up by less accurate (but reasonable) segmenters, to a surprising advantage. This suggests that words themselves might be too broad a notion to conveniently capture the general semantic meaning of Chinese text. Our research suggests machine learning techniques can play an important role in building adaptable information retrieval systems and different evaluation standards for word segmentation should be given to different applications.     

面向学习环境的大学生信息素养体系研究

大学生的学习是在一定的学习环境下进行的,信息素养体系则存在于学习环境之中并支撑其发展。文章尝试分析了大学生学习环境在信息时代的变化及特点,并在此基础上结合国内外高校信息素养教育实例,研究讨论适应学习和认知环境发展的新型高校信息素养体系,包括其目标、标准、作用、主要内容、方法/模式的变革与拓展,以推动信息素养成为支撑学习环境的元素养,并带动学习素养体系的全面发展。     

合作信息查寻与检索相关性判据的探索性因子分析

基于案例研究结果及早期研究成果设计合作信息查寻与检索相关性的判据量表,通过问卷调查获取高校及科研院所学生合作信息查寻与检索的相关性判据使用数据,利用临界值比较、内部一致性分析、均值比较、探索性因子分析等方法对这些数据进行量化分析,得出以下主要结论:合作相关性判据量表的项目共34项,分属于8个类别,分别为信息来源特征、信息内容有用性、信息索引特征、信息表现形式、信息质量、可获取性、信息结构特征与信息传播特征;8个类别可解释的方差变异约为60%,表明相关性判据不是相关判断的唯一标准或依据,还有其他因素影响用户的相关判断过程。