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Since researchers have utilized text signals to develop a mass of within-document visualization analysis tools for reading aid in a long document, there is an increasing need to study the relationship between readers’ behavior of using text signals for navigation and their reading performance in the tools. The purpose of this paper is to combine the text signals using behavior and reading performance in two kinds of analysis tools to verify their relationship and discover whether there is any efficient reading strategy when using text signals to navigate a long document.

The methodology is a case study. The authors reviewed related literature first. After explaining the design ideas, interface and functions of THC-DAT and BOOKMARK, which are two reading tools utilizing two main kinds of text signals, one utilizing topics and the other utilizing headings for reading aid, a case study was presented to collect click data on the text signals of participants and their reading effectiveness (score) and efficiency (time).

The results confirm that the text signals using behavior for navigation has a significant impact on reading efficiency and no impact on reading effectiveness in both BOOKMARK and THC-DAT. The discrete degree of clicks behavior on text signals has an impact on reading efficiency. The using behavior of different types of text signals has different impacts on reading efficiency.

Using text signals for navigation time evenly can help improve reading efficiency. And a basic strategy suggested to readers is focusing on reducing their time to find answers when using text signals for navigation in a long document. As to utilizing the two different kinds of text signals, readers can have different strategies. Accordingly, personalized recommendation based on interval of adjacent clicks will help to improve computer-aided reading tools.

This paper combines the text signals using behavior for navigation and reading performance in two kinds of visual analysis tools, studied the relationship between them and discovers some efficient reading strategies when using text signals for navigation to read a long document.

With a mass of electronic multi-topic documents available, there is an increasing need for evaluating emerging analysis tools to help users and digital libraries analyze these documents better. The purpose of this paper is to evaluate the effectiveness, efficiency and user satisfaction of THC-DAT, a within-document analysis tool, in reading a multi-topic document.

The authors reviewed related literature first, then performed a user-centered, comparative evaluation of two within-document analysis tools, THC-DAT and BOOKMARK. THC-DAT extracts a topic hierarchy tree using hierarchical latent Dirichlet allocation (hLDA) method and takes the context information into account. BOOKMARK provides similar functionality to the Table of Contents bookmarks in Adobe Reader. Three novel kinds of tasks were devised for participants to finish on two tools, with objective results to assess reading effectiveness and efficiency. And post-system questionnaires were employed to obtain participants’ subjective judgments about the tools.

The results confirm that THC-DAT is significantly more effective than BOOKMARK, while not inferior in efficiency. There is some evidence that suggests THC-DAT can slow down the process of approaching cognitive overload and improve users’ willingness to undertake difficult task. Based on qualitative data from questionnaires, the results indicate that users were more satisfied when using THC-DAT than BOOKMARK.

Adopting THC-DAT in digital libraries or electrical document reading systems contributes to promoting users’ reading performance, willingness to undertake difficult task and general satisfaction. Moreover, THC-DAT is of great value to addressing cognitive overload problem in the information retrieval field.

This paper evaluates a novel within-document analysis tool in analyzing a multi-topic document, and proved that this tool is superior to the benchmark in effectiveness and user satisfaction, and not inferior in efficiency.

The purpose of this paper is to propose a novel within-document analysis tool (DAT) topic hierarchy and context-based document analysis tool (THC-DAT) which enables users to interactively analyze any multi-topic document based on fine-grained and hierarchical topics automatically extracted from it. THC-DAT used hierarchical latent Dirichlet allocation method and took the context information into account so that it can reveal the relationships between latent topics and related texts in a document.

The methodology is a case study. The authors reviewed the related literature first, then utilized a general “build and test” research model. After explaining the model, interface and functions of THC-DAT, a case study was presented using a scholarly paper that was analyzed with the tool.

THC-DAT can organize and serve document topics and texts hierarchically and context based, which overcomes the drawbacks of traditional DATs. The navigation, browse, search and comparison functions of THC-DAT enable users to read, search and analyze multi-topic document efficiently and effectively.

It can improve the document organization and services in digital libraries or e-readers, by helping users to interactively read, search and analyze documents efficiently and effectively, exploringly learn about unfamiliar topics with little cognitive burden, or deepen their understanding of a document.

This paper designs a tool THC-DAT to analyze document in a THC way. It contributes to overcoming the coarse-analysis drawbacks of existing within-DATs.

The technological revolution is affecting the structure, form and content of documents, reducing the effectiveness of traditional abstracts that, to some extent, are inadequate to the new documentary conditions. Aims to show the directions in which abstracting/abstracts can evolve to achieve the necessary adequacy in the new digital environments. Three researching trends are proposed: theoretical, methodological and pragmatic. Theoretically, there are some needs for expanding the document concept, reengineering abstracting and designing interdisciplinary models. Methodologically, the trend is toward the structuring, automating and qualifying of the abstracts. Pragmatically, abstracts networking, combined with alternative and complementary models, open a new and promising horizon. Automating, structuring and qualifying abstracting/abstract offer some short‐term prospects for progress. Concludes that reengineering, networking and visualising would be middle‐term fruitful areas of research toward the full adequacy of abstracting in the new electronic age.

This paper describes the use of fixed‐length character strings for controlling the size of indexing vocabularies in reference retrieval systems. Experiments with the Cranfield test collection show that trigram encoding of words performs noticeably better than the use of digrams; however, use of the least frequent digram in each term produces more acceptable results. Hashing of terms gives a better performance than that obtained from a vocabulary of comparable size produced by right‐hand truncation. The application of small indexing vocabularies to the sequential searching of large document files is discussed.

This article reviews the state of the art in automatic indexing, that is, automatic techniques for analysing and characterising documents, for manipulating their descriptions in searching, and for generating the index language used for these purposes. It concentrates on the literature from 1968 to 1973. Section I defines the topic and its context. Sections II and III consider work in syntax and semantics respectively in detail. Section IV comments on ‘indirect’ indexing. Section V briefly surveys operating mechanized systems. In Section VI major experiments in automatic indexing are reviewed, and Section VII attempts an overall conclusion on the current state of automatic indexing techniques.

This paper makes a case for the investigation of organizational paradoxes through the analysis of documents. After having presented what paradoxes are and the methodological challenges of studying them, the paper turns to document research, with emphasis on its potential contribution to paradox research. More specifically, document research typically provides ready-to-code data in a nonintrusive manner, allowing for the potential longitudinal, multilevel and multivoice analysis of organizational paradoxes and their management, in practice. To illustrate this, the purpose of this paper is to explore exemplar research based on multiple approaches to the study of different paradoxes in/around various documents and sets a research agenda.

Exemplar research on paradoxes using organizational documents as central data are presented. This highlights the range of documents and analytical strategies that can be used to explore organizations’ discursive management of paradoxes, as well as the roles documents can play in organizational contexts marked by different types of paradoxes.

A research agenda is developed, formulated around the needs to study paradoxes within documents and around them; grasp the discursive strategies deployed in documents to deal with paradoxes and/or the action of documents in contexts marked by paradoxes; follow the organizational processes involving documents, paying special attention to the paradoxes surrounding the development, adoption and appropriation of documents; and compare paradoxes in documents and those around the documents’ mobilization.

Despite growing interest in organizational paradoxes, reflections on methodological approaches to exploring them remain scarce and alternative methods largely unexplored. This paper makes the following proposition: organizational documents (strategic plans, annual reports, policies, websites, etc.) can provide a valuable entry point to explore organizational paradoxes.

The impact of advances in information technology has been widespread, but the fundamentals of effective communication have remained unchanged. Improvements to documentation tools, such as computer platforms, word processing software and printer output devices, have enabled standards of experiment reporting to be raised. To cultivate further the quality presentation of scientific instrument waveform images, techniques of direct computer interface are presented. Taking advantage of the widespread support of the plotter communications language HPGL, a generalized method for image transfer and incorporation within document processors is developed and supported by examples. The possibility of image enhancement is explored in a computer program that also integrates the supervised transfer of instrument data. The technique has been successfully introduced into several undergraduate student‐centred work packages. Among the many benefits have been the significant improvements in the presentation of dissertations.

Purpose: As a result of the transition from the paradigm of ‘knowledge and skills’ learning to the university of uncertainty, the concept of VUCA has grown for the revision of various adaptive models of educational practices.

Need for Study: The primary goal is to explore the research field of the educational system and learning environments; the investigation of scientific knowledge is enabled by bibliometric analysis, revealing through it the fluctuations of the literature.

Methodology: To better view the historical evolution of publications in the educational system field, two data samples were integrated into this study, with the focus of the chapter being on the authors, keywords, articles, journals, subject analysis, word cloud analysis, and cluster analysis. The first includes 1,620 Web of Science-recorded documents published between 1991 and 2022, and the second sample comprises 159 Scopus-recorded papers published between 1978 and 2022.

Findings: The first empirical results show that interest in this subject escalated around 2008. The main concerns around this research field are the labour market, teaching-learning, technology, economic development, the medical field, and sustainability. After 2020, a new subject took amplitude, seemingly connected to the educational system and learning environment, that subject being ’COVID-19.

Practical Implications: The relationship between authors, keywords, and sources is illustrated through Sankey diagrams, from which valuable information can be extracted: nine of the Scopus authors have published articles in the ‘Journal of Higher Education Policy and Management’ documents that present the following list of keywords: ‘higher education’, ‘education’, ‘management’, ‘leadership’, and ‘tertiary education’.

This study updates the discussion on demand-pull attention as a source of radical product innovation. Demand-pull attention shows an ex ante alignment with market characteristics and needs as opposed to pushing resources toward markets. The authors suggest a holistic framework and specify three dimensions of demand-pull attention: anticipated or revealed market demand, market environment, and external economic environment. Based on a large German longitudinal panel consisting of 941 firm-year observations from 2003 to 2013, the authors conceptualized the measurement of demand-pull dimensions’ attention and radical product innovation using computer-aided text analysis of annual reports. The authors analyzed the relationship between the attention that a firm pays to different demand-pull dimensions and the firm’s strategic intention to radically innovate; thus, the authors actually focused on the cognitive sources of radical product innovations. This chapter suggests that radical product innovation activities are positively driven by attention toward the market environment and market demand orientation. However, the hypothesis, which assumed a negative relationship between attention toward the external economic environment and radical innovation, could not be significantly confirmed. This demands a closer look into the underlying decision processes of firms when deciding on radical product innovations. With the theoretical grounding on the attention-based view of the firm, the authors contribute to a better understanding of the role that organizational cognition plays in innovation processes.