Data Visualization as Participatory Research: A Model for Digital Collections to Inspire User-Driven Research

The emerging creative practices of digital collections are increasing in prominence thanks to the access to, and appeal of, data visualizations. Interactive data visualizations, such as a map, timeline, chart, graph, or artist’s rendering of data, enable users to pursue their own research interests within a collection and participate in new areas of research. Use of these data visualizations enhances the scope of the collection and enables a modern and diverse thematic collection to emerge. This article considers the question: Does the addition of data visualizations affect how users participate with a research collection? Impacts on collection development, application of user-centered design, and analysis of users’ exploratory strategies are discussed. Examples of data visualizations used in digital humanities projects and digital collections are presented as case studies.     

协同搜索过程中用户交流内容与模式研究

[目的/意义]旨在分析协同搜索用户在信息搜索任务过程中的交流内容与模式,从而理解协同搜索用户的关注重点与搜索过程。[研究设计/方法]基于书籍交互检索平台(CLEF-Social Book Search)设计实验,共招募18名被试完成两种搜索任务,通过录音记录对话并对其进行编码和分析,总结交流内容特征和模式。结合任务类型、认知类型组合、服务器记录的搜索交互行为日志以及问卷收集的搜索体验进行了探索分析。[结论/发现]从交流内容上看,协同搜索用户主要理解与评判书目信息、商讨搜索任务计划;比起认知类型不同的用户,相同认知类型的用户在操作交互方面交流更多,在评判决策方面交流较少。交流模式依据讨论内容比重可分为理解评判型、评判主导型、均衡交流型三种,评判主导型用户的任务完成满意度最高。[创新/价值]协同搜索用户的交流反映出搜索过程中需要与同伴商讨协同的焦点,也是需要系统提供协助的重点,给协同搜索系统设计提供一定参考。本研究针对协同搜索的交流内容设计的编码系统对相关的协同交流研究也有借鉴意义。     

Beyond traditional collaborative search: Understanding the effect of awareness on multi-level collaborative information retrieval

Although there has been a great deal of research into Collaborative Information Retrieval (CIR) and Collaborative Information Seeking (CIS), the majority has assumed that team members have the same level of unrestricted access to underlying information. However, observations from different domains (e.g. healthcare, business, etc.) have suggested that collaboration sometimes involves people with differing levels of access to underlying information. This type of scenario has been referred to as Multi-Level Collaborative Information Retrieval (MLCIR). To the best of our knowledge, no studies have been conducted to investigate the effect of awareness, an existing CIR/CIS concept, on MLCIR. To address this gap in current knowledge, we conducted two separate user studies using a total of 5 different collaborative search interfaces and 3 information access scenarios. A number of Information Retrieval (IR), CIS and CIR evaluation metrics, as well as questionnaires were used to compare the interfaces. Design interviews were also conducted after evaluations to obtain qualitative feedback from participants. Results suggested that query properties such as time spent on query, query popularity and query effectiveness could allow users to obtain information about team's search performance and implicitly suggest better queries without disclosing sensitive data. Besides, having access to a history of intersecting viewed, relevant and bookmarked documents could provide similar positive effect as query properties. Also, it was found that being able to easily identify different team members and their actions is important for users in MLCIR. Based on our findings, we provide important design recommendations to help develop new CIR and MLCIR interfaces.     

普通高校体育课编班教学改革实验研究

体育课教学是高等学校体育工作的核心。教学质量的好坏直接影响学生的体质。但是 ,现行的班级体育授课制仍然是沿袭以智力、高考分数为核心 ,方便文化课教学的编班制进行体育课教学 ,这无疑影响学生体质的发展和终身体育思想的形成 ,而且给体育课教学带来许多困难。因此 ,从发展学生体质和培养终身锻炼习惯的实际需要出发 ,打破单纯按智力、分数的分班制是当前高校体育教学工作中亟待解决的问题。     

高年级大学生课外体育活动参与特征调研

采用问卷调查、文献资料调研、数理统计等方法 ,对高年级大学生课外体育活动参与特征进行了分析与研究。结果发现 ,目前高年级大学生参与课外体育活动的人数量少 ,体育活动项目多样化 ,校园为主要的活动场所 ,每周活动次数 1～ 2次为主 ,每次活动时间 6 0 min以上 ,以中等活动负荷为主 ,呈多元化的活动目的动机 ,活动受主、客观因素的影响。据此提出了一些对策和建议。     

关于阶级及其相关问题的认识

阶级概念具有二重性 ,一方面是从阶层的角度揭示社会分工对社会发展的必要性 ;另一方面揭示由于社会分工的发展而产生了剥削者和被剥削者的对立。这两方面是统一的 ,任何撇开其中一方而强调另一方面的做法都是错误的。     

大学生课余体育锻炼现状的调查分析

课余体育锻炼是学校体育的重要组成部分，也是大学生健康生活方式的重要内容。通过问卷调查、文献资料和数理统计等方法，对大学生课余体育锻炼的现状进行了调查与分析，对调查中反映出来的一些主要问题进行了分析，并有针对性地提出了建议。     

学校体育及身体保健设问精解

针对学校体育及身体保健方面许多常识性问题上存在的认识偏误，设置40问并从体育基本理论的高度分别进行了简明解说。     

A Corpus-Based Learning Method of Compound Noun Indexing Rules for Korean

In Korean information retrieval, compound nouns play an important role in improving precision in search experiments. There are two major approaches to compound noun indexing in Korean: statistical and linguistic. Each method, however, has its own shortcomings, such as limitations when indexing diverse types of compound nouns, over-generation of compound nouns, and data sparseness in training. In this paper, we propose a corpus-based learning method, which can index diverse types of compound nouns using rules automatically extracted from a large corpus. The automatic learning method is more portable and requires less human effort, although it exhibits a performance level similar to the manual-linguistic approach. We also present a new filtering method to solve the problems of compound noun over-generation and data sparseness.     

Measuring Search Engine Quality

The effectiveness of twenty public search engines is evaluated using TREC-inspired methods and a set of 54 queries taken from real Web search logs. The World Wide Web is taken as the test collection and a combination of crawler and text retrieval system is evaluated. The engines are compared on a range of measures derivable from binary relevance judgments of the first seven live results returned. Statistical testing reveals a significant difference between engines and high intercorrelations between measures. Surprisingly, given the dynamic nature of the Web and the time elapsed, there is also a high correlation between results of this study and a previous study by Gordon and Pathak. For nearly all engines, there is a gradual decline in precision at increasing cutoff after some initial fluctuation. Performance of the engines as a group is found to be inferior to the group of participants in the TREC-8 Large Web task, although the best engines approach the median of those systems. Shortcomings of current Web search evaluation methodology are identified and recommendations are made for future improvements. In particular, the present study and its predecessors deal with queries which are assumed to derive from a need to find a selection of documents relevant to a topic. By contrast, real Web search reflects a range of other information need types which require different judging and different measures.