DIGITALISED DELIVERY OF LANGUAGE. AN APPROACH TOWARDS MACHINE TRANSLATION TECHNOLOGY

Unquestionably, in today’s language professionals, the use of information and communication technology (ICT) is already taken for granted and electronic handling as well as digitalized delivery of language services are standard client facilities. The present paper, while taking into the discussion the progressive stages of machine-assisted human translation (MAHT) and human-assisted machine translation (HAMT), analyses the present-day realities of Machine Translation

Strategic use of E-Commerce in the Transformation of the Publishing Industry

The intent of this paper is to explore the strategic use of e-commerce in the transformation of the publishing industry. The first section of the paper explores the strategic use of e-commerce in the transformation of the publishing industry from a single distribution channel mass producer of printed books to a multiple distribution channel that will include e-books and “print on demand” technologies. Emphasis is placed on management strategies in the use of new information technologies in the global marketplace. The second section of this paper discusses the shift of competitive power among the various tiers along the publishing industry supply chain including the current developments in electronic publishing from the vantage point of the stakeholders The implications and likely scenario awaiting the future business environment of the publishing industry is presented in the third section of this paper

COSPO/CENDI Industry Day Conference

The conference's objective was to provide a forum where government information managers and industry information technology experts could have an open exchange and discuss their respective needs and compare them to the available, or soon to be available, solutions. Technical summaries and points of contact are provided for the following sessions: secure products, protocols, and encryption; information providers; electronic document management and publishing; information indexing, discovery, and retrieval (IIDR); automated language translators; IIDR - natural language capabilities; IIDR - advanced technologies; IIDR - distributed heterogeneous and large database support; and communications - speed, bandwidth, and wireless

English for Information Technology: History and Types of a Computer

Навчальний посібник призначений для аудиторних і позааудиторних занять студентів першого курсу факультету інформатики та обчислювальної техніки. Видання складається з трьох розділів, які охоплюють професійно-орієнтовані теми: “History of Computers”, “Computers Today”, “Types of Computer”. Крім того, означене видання містить: секцію для перевірки залишкових знань, два робочі аркуші для закріплення в умовах парної роботи пройденого матеріалу; чотири додатки з поясненням граматичних явищ; список слів та абревіатур. Представлені в посібнику вправи спрямовано на розвиток та вдосконалення вмінь усного і писемного мовлення, читання, аудіювання та перекладу. Мета навчального посібника – розширити професійний тезаурус студентів, формувати навички роботи з автентичними матеріалами, сприяти розвитку професійно-орієнтованої комунікативної компетентності.This study e-book is intended for classroom and individual work with first-year students of the faculty of informatics and computer science. It consists of three units which comprise vocationally-oriented topics such as “History of Computers”, “Computers Today”, “Types of Computer” and has a revision section. In addition, there are two worksheets useful for pair work, four appendices with grammar reference, word list and abbreviations glossary. The main goal of the publication is to develop future IT specialists’ competences in English speaking, listening, reading, writing and improve their translation skills. This e-book has been designed to help students expand their job-related vocabulary, develop their vocationally-oriented communicative competence as well as accustom students to work with authentic English texts

Special Libraries, March 1968

Volume 59, Issue 3https://scholarworks.sjsu.edu/sla_sl_1968/1002/thumbnail.jp

Investigating German Higher Education Institutions\u27 Transfer Activities: New Measurements Based on Web Mining

In recent years, higher education institutions (HEI) have expanded their involvement in diverse transfer activities (TA), extending beyond traditional teaching and research roles. These TA are often heterogeneous and informal, which makes measuring their full scope and effects challenging. In this article, we propose a new and straightforward to implement approach for mastering this task. In a first step, we theoretically derive three different dimensions of transfer, namely the transfer of knowledge, technology and personnel. For each of these categories, we develop an artificial intelligence (AI) optimized keyword list. Finally, we use these lists and apply web mining techniques and natural language processing (NLP) to measure TA from German HEI. To this end, we analyze a total of 299,229 texts from 376 German HEI websites. Our study shows that our proposed approach represents an effective and valuable tool for measuring TA from HEI and provides a foundation for further research

Application of pre-training and fine-tuning AI models to machine translation: a case study of multilingual text classification in Baidu

With the development of international information technology, we are producing a huge amount of information all the time. The processing ability of information in various languages is gradually replacing information and becoming a rarer resource. How to obtain the most effective information in such a large and complex amount of multilingual textual information is a major goal of multilingual information processing. Multilingual text classification helps users to break the language barrier and accurately locate the required information and triage information. At the same time, the rapid development of the Internet has accelerated the communication among users of various languages, giving rise to a large number of multilingual texts, such as book and movie reviews, online chats, product introductions and other forms, which contain a large amount of valuable implicit information and urgently need automated tools to categorize and process those multilingual texts. This work describes the Natural Language Process (NLP) sub-task known as Multilingual Text Classification (MTC) performed within the context of Baidu, a Chinese leading AI company with a strong Internet base, whose NLP division led the industry in deep learning technology to go online in Machine Translation (MT) and search. Multilingual text classification is an important module in NLP machine translation and a basic module in NLP tasks. It can be applied to many fields, such as Fake Reviews Detection, News Headlines Categories Classification, Analysis of positive and negative reviews and so on. In the following work, we will first define the AI model paradigm of 'pre-training and fine-tuning' in deep learning in the Baidu NLP department. Then investigated the application scenarios of multilingual text classification. Most of the text classification systems currently available in the Chinese market are designed for a single language, such as Alibaba's text classification system. If users need to classify texts of the same category in multiple languages, they need to train multiple single text classification systems and then classify them one by one. However, many internationalized products do not have a single text language, such as AliExpress cross-border e-commerce business, Airbnb B&B business, etc. Industry needs to understand and classify users’ reviews in various languages, and have conducted in-depth statistics and marketing strategy development, and multilingual text classification is particularly important in this scenario. Therefore, we focus on interpreting the methodology of multilingual text classification model of machine translation in Baidu NLP department, and capture sets of multilingual data of reviews, news headlines and other data for manual classification and labeling, use the labeling results for fine-tuning of multilingual text classification model, and output the quality evaluation data of Baidu multilingual text classification model after fine-tuning. We will discuss if the pre-training and fine-tuning of the large model can substantially improve the quality and performance of multilingual text classification. Finally, based on the machine translation-multilingual text classification model, we derive the application method of pre-training and fine-tuning paradigm in the current cutting-edge deep learning AI model under the NLP system and verify the generality and cutting-edge of the pre-training and fine-tuning paradigm in the deep learning-intelligent search field.Com o desenvolvimento da tecnologia de informação internacional, estamos sempre a produzir uma enorme quantidade de informação e o recurso mais escasso já não é a informação, mas a capacidade de processar informação em cada língua. A maior parte da informação multilingue é expressa sob a forma de texto. Como obter a informação mais eficaz numa quantidade tão considerável e complexa de informação textual multilingue é um dos principais objetivos do processamento de informação multilingue. A classificação de texto multilingue ajuda os utilizadores a quebrar a barreira linguística e a localizar com precisão a informação necessária e a classificá-la. Ao mesmo tempo, o rápido desenvolvimento da Internet acelerou a comunicação entre utilizadores de várias línguas, dando origem a um grande número de textos multilingues, tais como críticas de livros e filmes, chats, introduções de produtos e outros distintos textos, que contêm uma grande quantidade de informação implícita valiosa e necessitam urgentemente de ferramentas automatizadas para categorizar e processar esses textos multilingues. Este trabalho descreve a subtarefa do Processamento de Linguagem Natural (PNL) conhecida como Classificação de Texto Multilingue (MTC), realizada no contexto da Baidu, uma empresa chinesa líder em IA, cuja equipa de PNL levou a indústria em tecnologia baseada em aprendizagem neuronal a destacar-se em Tradução Automática (MT) e pesquisa científica. A classificação multilingue de textos é um módulo importante na tradução automática de PNL e um módulo básico em tarefas de PNL. A MTC pode ser aplicada a muitos campos, tais como análise de sentimentos multilingues, categorização de notícias, filtragem de conteúdos indesejados (do inglês spam), entre outros. Neste trabalho, iremos primeiro definir o paradigma do modelo AI de 'pré-treino e afinação' em aprendizagem profunda no departamento de PNL da Baidu. Em seguida, realizaremos a pesquisa sobre outros produtos no mercado com capacidade de classificação de texto — a classificação de texto levada a cabo pela Alibaba. Após a pesquisa, verificamos que a maioria dos sistemas de classificação de texto atualmente disponíveis no mercado chinês são concebidos para uma única língua, tal como o sistema de classificação de texto Alibaba. Se os utilizadores precisarem de classificar textos da mesma categoria em várias línguas, precisam de aplicar vários sistemas de classificação de texto para cada língua e depois classificá-los um a um. No entanto, muitos produtos internacionalizados não têm uma única língua de texto, tais como AliExpress comércio eletrónico transfronteiriço, Airbnb B&B business, etc. A indústria precisa compreender e classificar as revisões dos utilizadores em várias línguas. Esta necessidade conduziu a um desenvolvimento aprofundado de estatísticas e estratégias de marketing, e a classificação de textos multilingues é particularmente importante neste cenário. Desta forma, concentrar-nos-emos na interpretação da metodologia do modelo de classificação de texto multilingue da tradução automática no departamento de PNL Baidu. Colhemos para o efeito conjuntos de dados multilingues de comentários e críticas, manchetes de notícias e outros dados para classificação manual, utilizamos os resultados dessa classificação para o aperfeiçoamento do modelo de classificação de texto multilingue e produzimos os dados de avaliação da qualidade do modelo de classificação de texto multilingue da Baidu. Discutiremos se o pré-treino e o aperfeiçoamento do modelo podem melhorar substancialmente a qualidade e o desempenho da classificação de texto multilingue. Finalmente, com base no modelo de classificação de texto multilingue de tradução automática, derivamos o método de aplicação do paradigma de pré-formação e afinação no atual modelo de IA de aprendizagem profunda de ponta sob o sistema de PNL, e verificamos a robustez e os resultados positivos do paradigma de pré-treino e afinação no campo de pesquisa de aprendizagem profunda

Four Shades of Gray

This first book-length analysis of Amazon's Kindle explores the platform's technological, bibliographical, and social impact on publishing. Four Shades of Gray offers the first book-length analysis of Amazon's Kindle and its impact on publishing. Simon Peter Rowberry recounts how Amazon built the infrastructure for a new generation of digital publications, then considers the consequences of having a single company control the direction of the publishing industry. Exploring the platform from the perspectives of technology, texts, and uses, he shows how the Kindle challenges traditional notions of platforms as discrete entities. He argues that Amazon's influence extends beyond “disruptive technology” to embed itself in all aspects of the publishing trade; yet despite industry pushback, he says, the Kindle has had a positive influence on publishing. Rowberry documents the first decade of the Kindle with case studies of Kindle Popular Highlights, an account of the digitization of books published after 1922, and a discussion of how Amazon's patent filings reflect a shift in priorities. Rowberry argues that while it was initially convenient for the book trade to outsource ebook development to Amazon, doing so has had adverse consequences for publishers in the mid- and long term, limiting opportunities for developing an inclusive and forward-thinking digital platform. While it has forced publishers to embrace digital forms, the Kindle has also empowered some previously marginalized readerships. Although it is still too early to judge the long-term impact of ebooks compared with that of the older technologies of clay tablets, the printing press, and offset printing, the shockwaves of the Kindle continue to shape publishing