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Organizations have been challenged to identify antecedents to improved employee adjustment to the work environment changes that arose in the wake of the COVID-19 global pandemic. This study aims to explore the effect of multilingualism on employee ability to adjust to workplace changes based on the concept that multilinguals have been found to switch between tasks more efficiently as compared to monolinguals.

Applying a sequential explanatory mixed methods research approach, quantitative performance evaluation data on 207 credit union employees is analyzed using hierarchical linear modeling to predict employee performance, and thematic analysis of qualitative data representing the adjustment narratives of six monolingual and six multilingual employees within the sample is conducted, corresponding to the period during which employees were adjusting to broad workplace changes after the onset of the global pandemic.

The results suggest greater predicted improvement in the performance of multilingual employees. Reliance on the task-switching ability associated with multilingualism is found to be the primary self-evaluative factor for successful change adjustment among multilingual employees.

In light of work performance benefits identified in this study, organizations may consider multilingualism as a characteristic preceding better adjustment to organizational change, and not simply as a skill applicable to tasks requiring language proficiency, suggesting practical implications for human resource and organizational management.

This is the first sequential explanatory study focusing on the task-switching ability of multilinguals as an antecedent to change adjustment evidenced by improved work performance within an organizational context.

The Central Medical Library (CMK) at the Faculty of Medicine of the University of Ljubljana, Slovenia, created its Web site in 1997 and has since then been actively involved in its maintenance and improvement. The analysis of Web site usage, which was performed using different data‐mining methods, revealed an increasing interest among the Slovene biomedical community. Patrons have often complained to librarians about information overload and difficulty in following all the Web site’s enhancements. This situation called for a dynamic restructuring of the CMK Web site. Such problems are often solved with customisable and personalised library portals. Having limited financial and human resources, it was decided to customise and extend an existing library portal software solution (MyLibrary from North Carolina State University). The MyLibrary portal for the CMK was not only customised, but some important new functionality, most notably multilingual support, was added. This experience of developing a personalised library portal could be of interest to most libraries that offer information in at least two languages.

Multilingual meetings continue to be a problem in business communication due to the necessity to translate between different natural language pairs. The paper has developed a new electronic meeting technology that automatically translates comments written in any of 41 languages (e.g. French, Chinese, etc.). The purpose of this paper is to quickly and accurately show on each user's terminal in his or her own native language all comments contributed by the group written in several different tongues.

A prototype system, Polyglot II, utilizes instant messaging on Microsoft Windows PCs to exchange comments between client personal computers and a server which in turn, calls the Google Translate API for each translation. In an attempt to measure the accuracy, reverse translations are conducted, e.g. English to French to English, because of the lack of human experts fluent in all of the languages. The final English translations are analyzed for comprehension by 240 college business students.

This paper uses reverse translations on 32 of the languages (all that are available at the time of the analysis) with historical transcripts of English text, including grammatical errors. Results show an overall comprehension accuracy of 86 percent for all languages. Italian is the most accurate, and Hindi is the least.

While other multilingual meeting technologies have been developed, this system provides automatic support for the most languages and is perhaps the most accurate.

The purpose of this explorative research study is to focus on the implementation of semantic Web technology on agriculture domain of e-governance data. The study contributes to an understanding of problems and difficulties in implantations of unstructured and unformatted unique datasets of multilingual local language-based electronic dictionary (IndoWordnet).

An approach to an implementation in the perspective of conceptual logical concept to realization of agriculture-based terms and terminology extracted from linked multilingual IndoWordNet while maintaining the support and specification of the World Wide Web Consortium (W3C) standard of semantic Web technology to generate ontology and uniform unicode structured datasets.

The findings reveal the fact about partial support of extraction of terms, relations and concepts while linking to IndoWordNet, resulting in the form of SynSets, lexical relations of Words and relations between themselves. This helped in generation of ontology, hierarchical modeling and creation of structured metadata datasets.

IndoWordNet has limitations, as it is not fully revised version due to diversified cultural base in India, and the new version is yet to be released in due time span. As mentioned in Section 5, implications of these ideas and experiments will have good impact in doing more exploration and better applications using such wordnet.

Language developer tools and frameworks have been used to get tagged annotated raw data processed and get intermediate results, which provides as a source for the generation of ontology and dynamic metadata.

The results are expected to be applied for other e-governance applications. Better use of applications in social and government departments.

The authors have worked out experimental facts and raw information source datasets, revealing satisfactory results such as SynSets, sensecount, semantic and lexical relations, class concepts hierarchy and other related output, which helped in developing ontology of domain interest and, hence, creation of a dynamic metadata which can be globally used to facilitate various applications support.

The main objective of the paper is to assess selected taxonomy building tools to review their features and capabilities for supporting development and deployment of taxonomy functions.

A checklist of desirable features and capabilities of taxonomy tools was used for assessment focusing on development, deployment, display, and information environment supported. White papers and product information datasheets on vendor sites were consulted to analyze features and capabilities of selected taxonomy tools.

The review indicates that more than 50 per cent of the selected tools support automatic and hybrid taxonomy building; about 80 per cent allow import and export of taxonomies and vocabularies; and all tools reviewed support classification and tagging. User interfaces, for maintenance, and display in facets, are supported by some tools, while, some have also integrated other visualization tools, or modules to provide clear representation of contents, and relationships.

Analysis is based on review of white papers and product information sheets and is therefore limited to indication of availability features and capabilities. The review does not assess performance of tools which would require use of tools and feedback from actual users.

The checklist used for assessment provides a useful template for organizations interested in assessing tools for taxonomy implementation. A summary of features and capabilities of selected taxonomy tools may also be useful in selecting tools for taxonomy application projects.

Little research has been reported in the literature on assessment methodology and evaluation of taxonomy tools. This study makes a good contribution to the literature on this important aspect of research and makes available useful practical information as well.

This paper discusses Internet‐based e‐content management. Specifically, this paper reviews the technologies, the criteria, and the issues and concerns in content repository (how content can be stored and retrieved), content contribution (how content can be created/digitized), workflow (content management), automation services, and lifecycle of automation services for controlling and managing content and processes. It presents an overview on the current available products and their applications in digital library deployment. Finally, issues, concerns, and challenges facing academic libraries are discussed.

Many open source software packages are available for organizations and individuals to create digital libraries (DLs). However, a simple to use instrument to evaluate these DL software packages does not exist. The objectives of the present work are to develop a checklist for DL evaluation and use this checklist on four DL software packages.

Features that characterized “good” open source DL software were determined from the literature. First identified were essential categories of features that DL software should possess. These categories were then decomposed into supporting features. From these, a checklist that covered all such features was developed. The checklist was then used to evaluate four popular open source DL software packages (CDSware, EPrints, Fedora, and Greenstone) for the purposes of assessing suitability for use in a DL project to be undertaken by the authors.

A checklist consisting of 12 categories of items was developed. Using this, Greenstone was found to be the best performer, followed by CDSware, Fedora and EPrints. Greenstone was the only software package that consistently fulfilled the majority of the criteria in many of the checklist categories. In contrast, EPrints was the worst performer due to its poor support for certain features deemed important in our checklist, and a total absence of functionality in other categories.

The present work attempts to develop a comprehensive checklist for assessing DLs. Its flexibility allows users to tailor it to accommodate new categories, items and weighting schemes to reflect the needs of different DL implementations.

The purpose of this paper is to analyse the paradigm shift of library automation to resource discovery by exploring the applications of resource discovery. The present status of India on adapting resource discovery applications is discussed.

An evaluative method to examine the status quo of India automation and resource discovery scenario is drawn with a related literature review. Moreover, various pertinent global challenges of embracing discovery tools in the digital environment are highlighted.

The growth of the Indian library automation industry is booming. However, library software adaptation, next‐generation catalogue enhancements and community development avenues are dearth, seemingly remote and far from satisfactory.

The paper focuses on the emerging scenario of resource discovery applications with an overview of global challenges.

When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals are primarily based on manual matching of similar topics, discipline areas and keywords declared by project applicants. When the number of proposals increases, this task becomes complex and requires excessive time. This paper aims to demonstrate how to effectively use the rich information in the titles and abstracts of Turkish project proposals to group them automatically.

This study proposes a model that effectively groups Turkish project proposals by combining word embedding, clustering and classification techniques. The proposed model uses FastText, BERT and term frequency/inverse document frequency (TF/IDF) word-embedding techniques to extract terms from the titles and abstracts of project proposals in Turkish. The extracted terms were grouped using both the clustering and classification techniques. Natural groups contained within the corpus were discovered using k-means, k-means++, k-medoids and agglomerative clustering algorithms. Additionally, this study employs classification approaches to predict the target class for each document in the corpus. To classify project proposals, various classifiers, including k-nearest neighbors (KNN), support vector machines (SVM), artificial neural networks (ANN), classification and regression trees (CART) and random forest (RF), are used. Empirical experiments were conducted to validate the effectiveness of the proposed method by using real data from the Istanbul Development Agency.

The results show that the generated word embeddings can effectively represent proposal texts as vectors, and can be used as inputs for clustering or classification algorithms. Using clustering algorithms, the document corpus is divided into five groups. In addition, the results demonstrate that the proposals can easily be categorized into predefined categories using classification algorithms. SVM-Linear achieved the highest prediction accuracy (89.2%) with the FastText word embedding method. A comparison of manual grouping with automatic classification and clustering results revealed that both classification and clustering techniques have a high success rate.

The proposed model automatically benefits from the rich information in project proposals and significantly reduces numerous time-consuming tasks that managers must perform manually. Thus, it eliminates the drawbacks of the current manual methods and yields significantly more accurate results. In the future, additional experiments should be conducted to validate the proposed method using data from other funding organizations.

This study presents the application of word embedding methods to effectively use the rich information in the titles and abstracts of Turkish project proposals. Existing research studies focus on the automatic grouping of proposals; traditional frequency-based word embedding methods are used for feature extraction methods to represent project proposals. Unlike previous research, this study employs two outperforming neural network-based textual feature extraction techniques to obtain terms representing the proposals: BERT as a contextual word embedding method and FastText as a static word embedding method. Moreover, to the best of our knowledge, there has been no research conducted on the grouping of project proposals in Turkish.

Knowledge management (KM) is an important consideration in e‐government portals to ensure that knowledge flows efficiently between governments, individuals and organisations. A crucial aspect of e‐government portals that has not been addressed adequately is the extent to which KM mechanisms have been implemented. Specifically, the authors argue that appropriate KM mechanisms are necessary to support the access, creation and transfer of knowledge between these portals and their users. The paper aims to propose an evaluation model for this purpose by first defining the main KM mechanisms and then burrowing deeper into their constituent dimensions.

An evaluation model known as knowledge access, creation and transfer (K‐ACT) is presented which identifies three KM mechanisms for portals: knowledge access, creation and transfer. Each mechanism is characterised by a set of dimensions and sub‐dimensions representing the tools and features for supporting that mechanism. The model was derived from an analysis of the literature and validated by two independent reviewers who were trained in information science, were familiar with the objectives of the project and understood the concepts underlying KM implementation in portals. Using this model, a checklist was developed and applied to 60 e‐government portals in the Asian and North American regions to investigate the extent to which these KM mechanisms have been implemented.

The findings indicate that, on average, e‐government portals featured only about 36 per cent of the KM mechanisms described in the model. Furthermore, no significant differences in the implementation of the KM mechanisms were found between the two regions' portals. The evaluation also offered potential areas for improvement based on the K‐ACT model.

The present work has developed an evaluation model known as K‐ACT which can be used to assess KM implementation gaps in e‐government portals. This model can also be generalised to other types of portals. The evaluation also provides insights into the state of KM processes in the portals of the Asian and North American regions.