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The recent report for the Commission of the European Communities on current multilingual activities in the field of scientific and technical information and the 1977 conference on the same theme both included substantial sections on operational and experimental machine translation systems, and in its Plan of action the Commission announced its intention to introduce an operational machine translation system into its departments and to support research projects on machine translation. This revival of interest in machine translation may well have surprised many who have tended in recent years to dismiss it as one of the ‘great failures’ of scientific research. What has changed? What grounds are there now for optimism about machine translation? Or is it still a ‘utopian dream’ ? The aim of this review is to give a general picture of present activities which may help readers to reach their own conclusions. After a sketch of the historical background and general aims (section I), it describes operational and experimental machine translation systems of recent years (section II), it continues with descriptions of interactive (man‐machine) systems and machine‐assisted translation (section III), (and it concludes with a general survey of present problems and future possibilities section IV).

The goal of a good computer interface is to provide a natural language help facility that allows new users to learn about the computer, its operating system in particular, and the important packages that are available for his use. The UNIX Consultant (UC) is an intelligent natural language interface designed to allow naive users to communicate with the UNIX operating system (of A.T. and T. Bell Laboratories) in ordinary English in as painless a way as possible. UC allows the user to engage in natural language dialogues with the operating system. He can query UC about how to do things in UNIX, ask about common names, formats, receive on‐line definitions of UNIX and get help debugging problems using UNIX commands.

This paper is the actualization of a researcher’s attempt to engage, both conceptually and methodologically, with the dynamic and ever-creative connections and forces associated with the schooling experiences of immigrant students. The research reported that in this paper comprises part of a three-year research project funded by Canada’s Social Sciences and Humanities Research Council and focuses on the interrelationships between immigration, technology and pop culture in a Canadian French-language secondary school. The paper aims to discuss this issue.

Drawing from new materialist thought, the experience of one immigrant student is put to work with(in) the Deleuzo–Guattarian concepts of agencement, machines, language and power (pouvoir, puissance) with(in) the rhizoanalysis of a short video clip provided by the student.

With(in) the rhizoanalysis, the publication machine emerges as a force that could potentially affect the expression of one’s becoming citizen, and hacking emerges as a force that could contribute to the destabilization of the publication machine’s power (pouvoir).

The originality of this paper is that readers are also invited to contribute to this experimentation in contact with the real.

This paper aims to develop a model to predict online review ratings from multiple sources, which can be used to detect fraudulent reviews and create proprietary rating indexes, or which can be used as a measure of selection in recommender systems.

This study applies machine learning and natural language processing approaches to combine features derived from the qualitative component of a review with the corresponding quantitative component and, therefore, generate a richer review rating.

Experiments were performed over a collection of hotel online reviews – written in English, Spanish and Portuguese – which shows a significant improvement over the previously reported results, and it not only demonstrates the scientific value of the approach but also strengthens the value of review prediction applications in the business environment.

This study shows the importance of building predictive models for revenue management and the application of the index generated by the model. It also demonstrates that, although difficult and challenging, it is possible to achieve valuable results in the application of text analysis across multiple languages.

The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing studies rarely take a perspective of educational technology application to evaluate the application of chatbots to educational contexts. This study aims to bridge the research gap by taking an educational perspective to review the existing literature on artificial intelligence chatbots.

This study combines bibliometric analysis and citation network analysis: a bibliometric analysis through visualization of keyword, authors, organizations and countries and a citation network analysis based on literature clustering.

Educational applications of chatbots are still rising in post-COVID-19 learning environments. Popular research issues on this topic include technological advancements, students’ perception of chatbots and effectiveness of chatbots in different educational contexts. Originating from similar technological and theoretical foundations, chatbots are primarily applied to language education, educational services (such as information counseling and automated grading), health-care education and medical training. Diversifying application contexts demonstrate specific purposes for using chatbots in education but are confronted with some common challenges. Multi-faceted factors can influence the effectiveness and acceptance of chatbots in education. This study provides an extended framework to facilitate extending artificial intelligence chatbot applications in education.

The authors have to acknowledge that this study is subjected to some limitations. First, the literature search was based on the core collection on Web of Science, which did not include some existing studies. Second, this bibliometric analysis only included studies published in English. Third, due to the limitation in technological expertise, the authors could not comprehensively interpret the implications of some studies reporting technological advancements. However, this study intended to establish its research significance by summarizing and evaluating the effectiveness of artificial intelligence chatbots from an educational perspective.

This study identifies the publication trends of artificial intelligence chatbots in educational contexts. It bridges the research gap caused by previous neglection of treating educational contexts as an interconnected whole which can demonstrate its characteristics. It identifies the major application contexts of artificial intelligence chatbots in education and encouraged further extending of applications. It also proposes an extended framework to consider that covers three critical components of technological integration in education when future researchers and instructors apply artificial intelligence chatbots to new educational contexts.

Following an outline of the organizational context of terminology work in the Commission, this paper considers the various types of computer application used, ranging from mainframe terminology databases (Eurodicautom) through documentary databases and wordprocessing software to specialized PC applications, with particular attention to current developments. An attempt is made to explain the factors leading to the development of an in‐house terminology management tool for a networked PC environment and the features of the package developed are reviewed. Consideration is also given to the lessons which others might draw from the Commission's experience.

‘The telling of this story’ wrote Gottfried Keller at the start of his Romeo und Julia auf dem Dorfe, ‘might seem to be merely pointless repetition.’ The writer of yet another paper on technical translations may feel himself in the same position. What can he say that has not already been said? Faced with this problem, I first thought to solve it by describing my own experiences in this field, since one of my functions as an information officer is to operate a translation service. I am therefore inviting you to follow the progress of a typical translation through our system at BP Research Centre from the initial request to the final evaluation. However, to prevent this talk from being too parochial, I shall try to relate each stage of the process to the wider issues involved.

Reports on ongoing research in developing generative process planning systems. Presents a feature‐based model for describing component geometry and its structural aspects (connectivity) and a hierarchical structure for form features definition and classification, as well as methods for representing the capabilities of machine tools. These models form the basis for decision making in the prototype process planning system GENPLAN. As an example, reports on how the models are being used for reasoning about component geometry and a linguistic approach that is adopted for machine tool selection in process planning.

The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications of the different building blocks with respect to market knowledge in B2B marketing and outlines avenues for future research.

The paper is conceptual and proposes a framework to explicate the phenomenon AI and its building blocks. It further provides a structured discussion of how AI can contribute to different types of market knowledge critical for B2B marketing: customer knowledge, user knowledge and external market knowledge.

The paper explains AI from an input–processes–output lens and explicates the six foundational building blocks of any AI system. It also discussed how the combination of the building blocks transforms data into information and knowledge.

Aimed at general marketing executives, rather than AI specialists, this paper explains the phenomenon artificial intelligence, how it works and its relevance for the knowledge-based marketing in B2B firms. The paper highlights illustrative use cases to show how AI can impact B2B marketing functions.

The study conceptualizes the technological phenomenon artificial intelligence from a knowledge management perspective and contributes to the literature on knowledge management in the era of big data. It addresses calls for more scholarly research on AI and B2B marketing.