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In the field of information retrieval, some multi‐lingual tools are being created to help the users to overcome the language barriers. Nevertheless, these tools are not developed completely and it is necessary to investigate more for their improvement and application. One of their main problems is the choice of the linguistic resources to offer better coverage and to solve the translation problems in the context of the multi‐lingual information retrieval. This paper aims to address this issue.

This research is focused on the analysis of resources used by the multi‐lingual question‐answering systems, which respond to users' queries with short answers, rather than just offering a list of documents related to the search. An analysis of the main publications about the multi‐lingual QA systems was carried out, with the aim of identifying the typology, the advantages and disadvantages, and the real use and trend of each of the linguistic resources and tools used in this new kind of system.

Five of the resources most used in the cross‐languages QA systems were identified and studied: databases, dictionaries, corpora, ontologies and thesauri. The three most popular traditional resources (automatic translators, dictionaries, and corpora) are gradually leaving a widening gap for others – such as ontologies and the free encyclopaedia Wikipedia.

The perspective offered by the translation discipline can improve the effectiveness of QA systems.

This paper aims to review current approaches to, and good practice in, information literacy (IL) development in multi-lingual and multi-cultural settings, with particular emphasis on provision for international students.

A selective and critical review of published literature is extended by evaluation of examples of multi-lingual IL tutorials and massive open online courses.

Multi-lingual literacy and multi-cultural IL are umbrella terms covering a variety of situations and issues. This provision is of increasing importance in an increasingly mobile and multi-cultural world. This paper evaluates current approaches and good practice, focussing on issues of culture vis-à-vis language; the balance between individual and group needs; specific and generic IL instruction; and models for IL, pedagogy and culture. Recommendations for good practice and for further research are given.

This is one of very few papers critically reviewing how IL development is affected by linguistic and cultural factors.

This paper aims to illustrate the scope and challenges of using computer-aided content analysis in international marketing with the aim to capture consumer sentiments about COVID-19 from multi-lingual tweets.

The study is based on some 35 million original COVID-19-related tweets. The study methodology illustrates the use of supervised machine learning and artificial neural network techniques to conduct extensive information extraction.

The authors identified more than two million tweets from six countries and categorized them into PESTEL (i.e. Political, Economic, Social, Technological, Environmental and Legal) dimensions. The extracted consumer sentiments and associated emotions show substantial differences across countries. Our analyses highlight opportunities and challenges inherent in using multi-lingual online sentiment analysis in international marketing. Based on these insights, several future research directions are proposed.

First, the authors contribute to methodology development in international marketing by providing a “use-case” for computer-aided text mining in a multi-lingual context. Second, the authors add to the knowledge on differences in COVID-19-related consumer sentiments in different countries. Third, the authors provide avenues for future research on the analysis of unstructured multi-media posts.

The purpose of this paper is to investigate the feasibility of creating a declarative user interface language suitable for rapid prototyping of mobile and Web apps. Moreover, this paper presents a new framework for creating responsive user interfaces using JavaScript.

Very little existing research has been done in JavaScript-specific declarative user interface (UI) languages for mobile Web apps. This paper introduces a new framework, along with several case studies that create modern responsive designs programmatically.

The fully implemented prototype verifies the feasibility of a JavaScript-based declarative user interface library. This paper demonstrates that existing solutions are unwieldy and cumbersome to dynamically create and adjust nodes within a visual syntax of program code.

This paper presents the Guix.js platform, a declarative UI library for rapid development of Web-based mobile interfaces in JavaScript.

The purpose of this paper is to highlight the use of big data through patentometric insights for R&D decision-making.

This study assesses the inventive activity through ‘big data’ patents, registered by inventors worldwide, using WIPO Patentscope database. The objective is to use the insights from patentometrics for R&D decision-making. The data from WIPO PatentScope (https://patentscope.wipo.int/search/en/search.jsf) was searched for current patent scenario in area of ‘big data’. The data was further organized and cleaned using the Google ‘OpenRefine’. Data was pre-processed to remove all null values. Cleaned data was analyzed using programming language ‘R’, MS Excel (charts and Pivot tables) and free data visualization tool called ‘Tableau Public’, to get insights for R&D decision-making.

The key insights included trends (patents with years of publication), top technologies trending the current space, top organizations leading in these technologies and the top inventors who are publishing patents in these technologies through leading organizations were drawn. Details in Section 5 in the paper.

Global patent data is multi-lingual and spreads across a set of multiple databases. Domain experts may be required to assess, identify and extract the relevant information for analysis and visualization of multi-lingual distributed data sets. Government organizations generally have multi-dimensional goals that may be more toward societal benefits. On the other hand, the commercial companies are more focused on profit. Therefore, the performance management process has to be really effective because it is critical for getting value in the government sector.

Insights from patent analytics serve as the important input to R&D managers as well as policymakers to assess the global needs to plan the national orientation according to the global market. This will help further for R&D projects prioritization, planning, budget allocations, human capital planning and other gamut of R&D management and decision-making.

Facilitation for R&D institutions (government as well as private) to formulate the research strategy for the domains or research areas to delve into. R&D decisions will be completely data-driven making them more accurate, reliable, valid and informed. These insights are very relevant for policymakers as well to facilitate the need assessment to determine the National priorities, make improvements in meeting societal country-level challenges during the resource allocation at top and subsequently at all other levels.

Data analytics of global patents in “big data” till 2019 to get insights to facilitate R&D decision-making.

Character coding systems such as ASCII and EBCDIC are unable to deal with the worldwide range of characters and so possible solutions, such as ISO 10646 and Unicode, involving 16‐bit codes have been suggested. The paper examines how libraries deal with multi‐lingual character sets and describes work being undertaken on the definition of a basic European character set as part of the National Bibliographies on CD‐ROM project being funded as part of the Commission of the European Communities Action Plan for Libraries.

Owing to the uneven distribution of annotated corpus among different languages, it is necessary to bridge the gap between low resource languages and high resource languages. From the perspective of entity relation extraction, this paper aims to extend the knowledge acquisition task from a single language context to a cross-lingual context, and to improve the relation extraction performance for low resource languages.

This paper proposes a cross-lingual adversarial relation extraction (CLARE) framework, which decomposes cross-lingual relation extraction into parallel corpus acquisition and adversarial adaptation relation extraction. Based on the proposed framework, this paper conducts extensive experiments in two tasks, i.e. the English-to-Chinese and the English-to-Arabic cross-lingual entity relation extraction.

The Macro-F1 values of the optimal models in the two tasks are 0.880 1 and 0.789 9, respectively, indicating that the proposed CLARE framework for CLARE can significantly improve the effect of low resource language entity relation extraction. The experimental results suggest that the proposed framework can effectively transfer the corpus as well as the annotated tags from English to Chinese and Arabic. This study reveals that the proposed approach is less human labour intensive and more effective in the cross-lingual entity relation extraction than the manual method. It shows that this approach has high generalizability among different languages.

The research results are of great significance for improving the performance of the cross-lingual knowledge acquisition. The cross-lingual transfer may greatly reduce the time and cost of the manual construction of the multi-lingual corpus. It sheds light on the knowledge acquisition and organization from the unstructured text in the era of big data.

The present situation concerning the use of different languages in data bases is outlined. It is somewhat analogous to that in the field of publishing, as English is the predominant carrier language used. Nevertheless, a number of monolingual data bases offer multilingual features, and there exist a few multi‐lingual data bases. This is already an indication that new tendencies are at work.