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Cet article compare deux campagnes d’annotation successives visant l’identification manuelle des occurrences de candidats termes relevant de la discipline scientifique dans laquelle s’inscrit l’article. Les deux campagnes se distinguent par leurs objectifs. La première visait l’enrichissement de terminologies existantes. La seconde avait le double objectif de comparer plusieurs environnements d’annotation (BRAT, GATE, GLOZZ) et de mesurer la difficulté de la tâche d’annotation en sciences humaines et sociales (SHS) par rapport aux sciences dites exactes. Les corpus produits ne permettant pas de comparer les deux campagnes directement, nous les exploitons comme corpus d’apprentissage dans une tâche test qui consiste à automatiser l’annotation manuelle. L’objectif est de savoir si le corpus de la seconde campagne permet d’augmenter les performances de la tâche test par rapport à celui de la première campagne. This paper compares two successive annotation campaigns aimed at manually identifying the occurrences of candidate terms that actually fall within the scientific domain of the annotated document. The two campaigns are distinguished by their objectives. The first aimed at the enrichment of existing terminological resources. The second had the dual objective of comparing several annotation tools (BRAT, GATE, GLOZZ) and measuring the difficulty of the annotation task in the human and social sciences compared to the so-called hard sciences. A direct comparison between both campaigns is not possible on the basis of the produced corpora. To do this, we use these corpora as learning corpus in the context of a test task. The role of this task is automate the manual annotation. The goal is to determine if the second corpus is of better quality than the first one with regards to the test task performances.

This paper compares two successive annotation campaigns aimed at manually identifying the occurrences of candidate terms that actually fall within the scientific domain of the annotated document. The two campaigns are distinguished by their objectives. The first aimed the enrichment of existing terminological resources. The second had the dual objective of comparing several annotation tools (BRAT, GATE, GLOZZ) and measuring the difficulty of the annotation task in the human and social sciences compared to the so-called hard sciences. A direct comparison between both campaigns is not possible on the basis of the produced corpora. To do this, we use these corpora like learning corpus in the context of a test task. The role of this task is to automatise the manual annotation. The goal is to determine if the second corpus is of better quality than the first one with regards to the test task performances., Cet article compare deux campagnes d'annotation successives visant l'identification manuelle des occurrences de candidats termes qui relèvent effectivement de la discipline scien-tifique de l'article considéré. Les deux campagnes se distinguent par leurs objectifs. La pre-mière visait l'enrichissement de terminologies existantes. La seconde avait le double objectif de comparer plusieurs environnements d'annotation (BRAT, GATE, GLOZZ), et de mesurer la dif-ficulté de la tâche d'annotation en sciences humaines et sociales par rapport aux sciences dites exactes. Les corpus produits ne permettant pas de comparer les deux campagnes directement, nous exploitons ces corpus comme corpus d'apprentissage dans une tâche test qui consiste à automatiser l'annotation manuelle. L'objectif est de savoir si le corpus de la seconde cam-pagne permet d'augmenter les performances de la tâche test par rapport à celui de la première campagne.

Prema Teoriji jezika u kontaku, prilagodba izvornog jezičnog modela u anglicizme provodi se na četiri razine, od kojih svaki ima svoju teoretsku osnovu. Na te četiri razine, tj. ortografskoj razini, fonološkoj razini, morfološkoj razini i semantičkoj razini, događaju se promjene koje definiraju oblik i značenje anglicizama na ruskom jeziku. Diplomski rad prikazuje i objašnjava adaptaciju posuđenica računalne terminologije iz engleskog u ruski jezik na morfološkoj razini. U procesu prijelaza modela u repliku, morfemi jezika davatelja usklađeni su s morfološkim sustavom jezika primatelja. Ta prilagodba ili supstitucija na morfološkoj razini prvenstveno se primjenjuje na osnovnom obliku posuđenice bez obzira kojoj vrsti riječi ona pripada, zatim na morfološke kategorije povezane s tom riječi, a zatim se nastavlja s promjenjivim oblicima posuđenice prema tome kojoj vrsti riječi pripada. U svojoj knjizi Teorija jezika u kontaktu, Rudolf Filipović navodi tri različite vrste adaptacije na morfološkoj razini, odnosno transmorfemizacije: nulta transmorfemizacija (prijenos slobodnog morfema iz jezika primatelja u jezik davatelj), kompromisna transmorfemizacija (prijenos stranog vezanog morfemskog sufiksa u jezik primatelj) i potpuna transmorfemizacija (zamjena sufiksa iz jezika davatelja s odgovarajućim sufiksom u jezik primatelj). According to the Theory of Languages in Contact, adaptation of original language model into anglicisms is carried on four levels, of which every one has its theoretic base. On that four levels, i.e. ortographical level, phonological level, morphological level and semantic level, changes which define form and meaning of anglicisms in Russian language are carried out. The diploma thesis presents and explains the adaptation of loanwords from computational terminology from English to Russian language on the morphological level. In the process of adaptation of a model into the replica, morphemes of the donor language are harmonized with the morphological system of the recipient language. That adaptation or substitution at the morphological level is applicable firstly on the basic form of loanword no matter which type of word it belongs to, and then on morphological categories associated with that word, and then continues with the changeable forms of loanword according to which type of words it belongs to. In his book Theory of Language in Contact, Rudolf Filipović cites three different types of adaptation on the morphological level, i.e., transmorphemization: zero transmorphemization (transfer of free morphemes from the recipient language to the donor language), compromise transmorphemization (transmission of the English bound morpheme to the recipient language) and complete transmorphemization (replacement of suffixes from the donor language with adequate suffix in the recipient language). Согласно Tеории языков в контакте, адаптация оригинальной языковой модели в англицизм осуществляется на четырех уровнях, из которых каждый имеет свою теоретическую базу. На этих четырех уровнях, то есть на орфографическом уровне, фонологическом уровне, морфологическом уровне и семантическом уровне, происходят изменения, которые определяют форму и значение англицизмов в русском языке. Дипломная работа показывает и объясняет адаптацию заимствованных слов компьютерной терминологии с английского языка на русский на морфологическом уровне. В процессе адаптации модели в реплику, морфемы языка-донора приспосабливаются к морфологической системе языка-реципиента. Эта адаптация или замещение на морфологическом уровне происходит, прежде всего, с основной формой заимствованного слова независимо от того, к какой части речи слово принадлежит, потом с морфологическими категориями, связанными с этим словом, а затем распространяется на изменяемые формы заимствованного слова, в соответствии с его частеречной принадлежностью. В своей книге Теория языков в контакте, Рудольф Филипович выделяет три различных типа адаптации морфологическом уровне, или трансморфемизации: нулевая трансморфемизация (перенос свободной морфемы из языка-донора в язык-реципиент), компромиссная трансморфемизация (перенос английских связанных морфем в язык-реципиент) и полная трансморфемизация (заменa суффиксa языка-донора соответствующим суффиксом языкa-реципиента ).

En esta presentación, mostraremos la metodología y los recursos utilizados en el desarrollo de Termonet, una herramienta para la consulta y verificación en corpus de los léxicos de especialidad incluidos en WordNet. Termonet realiza una identificación en WordNet de los synsets pertenecientes a un ámbito terminológico a partir de las relaciones léxico-semánticas establecidas entre los synsets, y valida los términos identificándolos en un corpus especializado desambiguado semánticamente. La construcción de esta herramienta forma parte de las tareas del proyecto de investigación SKATeR-UVigo, orientado al desarrollo y aplicación de recursos para el procesamiento lingüístico del gallego. In this presentation, we review the methodology and the resources used in the development of Termonet, a tool for checking and verifying in a corpus the specialty lexicons embedded in WordNet. This tool performs an identification of the synsets in WordNet belonging to a terminological domain from the lexical-semantic relations established among synsets, and validates the terms identifying them by means of a semantically disambiguated specialized corpus. The construction of this tool is part of the tasks of the SKATeR-UVigo research project, aimed at the development and application of resources for Galician language processing. Esta investigación se realiza en el marco del proyecto Adquisición de escenarios de conocimiento a través de la lectura de textos: Desarrollo y aplicación de recursos para el procesamiento lingüístico del gallego (SKATeR-UVigo) financiado por el Ministerio de Economía y Competitividad, TIN2012-38584-C06-04.

Knowledge is assumed by cognitive science to consist of concepts that are organised and maintained by complex processes taking place in human minds. These processes are not yet accessible directly. Language is still the primary medium for communicating knowledge and presumably linguistic objects and structures are expressions of knowledge and its organisation in mind. Collecting terms (i.e., creating a specialised vocabulary) and capturing their relationships are thus important mechanisms for distilling knowledge from specialised texts and for formalising it for machines. The approach taken in this thesis is to analyse the co-hyponymy relationships between terms as an organisational mechanism. Co-hyponyms are sets of lexical units sharing a common hypernym; bank and building society, for example, are co-hyponyms of the hypernym financial organisation. Analysing the co-hyponymy relationships between terms is important because it bridges the semantic gap between a) specialised lexical knowledge, b) the quantitative interpretation of meanings in specialised discourse, and c) machine-accessible conceptualisation of knowledge. This thesis proposes the use of a vector-based distributional representation of terms in order to construct a quantitative conceptual model of kinds-sorts in a given field of knowledge. Among empirical methods for analysing linguistic structures, distributional approaches to semantics encode language data to models that should correspond to the meanings of linguistic entities. The meaning of an entity, such as a word or a phrase, is assumed to be a function of its statistical distribution in contexts. In order to use these methods we thus need to define (a) the contexts, that is, which statistical information must be collected; and (b) the functions, that is, how this information must be used to correlate with a meaning. This thesis is a study of corpus-based distributional methods for characterising co-hyponymy between terms. Terms are represented as vectors to form a so-called term-space model. To obviate the curse of dimensionality and to facilitate the construction of models, novel methods employing sparse random projections are proposed. Random Manhattan indexing is used to construct L1-normed spaces and random indexing for L2-normed spaces. Following these steps a memory-based classifier exploits the distance between vectors to identify the presence of targeted co-hyponymy relationships. An evaluation is also performed to assess any reciprocal influences of the method's parameters on its performance. Userfriendliness, flexibility in updating and maintenance, and an innate capacity to resemble conceptual structures in a domain knowledge are the advantages of this method.

[Resumo] Neste artigo amosaremos as diferentes metodoloxías e os recursos que se utilizaron durante o proceso de elaboración de Galnet, a versión galega de WordNet. Presentarase tamén a ferramenta Termonet, desenvolvida para a consulta e verificación en corpus de léxicos de especialidade extraídos de WordNet. Por último, describirase a experimentación orientada ao deseño automático de áreas semánticas mediante a explotación das relacións léxico-semánticas de WordNet [Abstract] In this article we will present the different methodologies and resources which were used during the elaboration process of GalNet, the Galician version of WordNet. We will also present Termonet, a tool developed to consult and verify specialty lexicons extracted from WordNet in corpora. Finally, we will describe an experiment oriented to the automatic shaping of semantic areas by using lexical-semantic relationships in WordNet

The paper deals with problems of anglicism adaptation in the Croatian computational terminology. Its aim was to analyse orthographic and morphological adaptation of 45 computational anglicisms found in Croatian computer magazines, i.e. to see to which extent those terms adapted to orthographic and morphological systems of the Croatian language. As the theoretical background of the research, Filipović's work in the field of languages in contact was used. On the orthographic level, anglicisms were classified into four categories according to how the orthography of their basic forms was created: a) pronunciation of the model, b) orthography of the model, c) combination of pronunciation and orthography of the model, d) according to the impact of the intermediary language. Furthermore, morphological adaptation was divided into three stages: a) zero transmorphemisation ; b) compromise transmorphemisation and c) complete transmorphemisation. It can be concluded that majority of anglicisms are not fully adapted to the Croatian language system and that they mostly remained at the level of compromise replicas, both on orthographic and morphological level.

The number of specialized terms continuously grows in the documents, at a pace which is difficult to follow for the terminology standardization organizations. The methods of bilingual term lexicon construction from the text corpora provide solutions. Our thesis falls into this topic: bilingual lexicon acquisition from comparable corpora. Compound terms (terms containing several roots, but a single graphical unit) are challenging for natural language processing applications. Given their graphical form, they are often handled in the same manner as single word terms, which prevents from apprehending their semantic complexity. Our involvement in an automatical terminology extraction evaluation allowed us to check our hypothesis: compound terms need a particular processing in a multilingual context.We proposed a method for compound terms recognition and splitting, which combines language-independent and language-specific features. It allowed us to obtain results comparable with those of state-of-the-art methods, while validating on a sample of languages from several families (germanic, slavic, romance languages), and adapting the method to specialized domains (tested on two domains: wind energy and breast cancer). We used the produced segmentations for compositional translation of compound terms, and for their multi-word variant recognition in the specialized texts. These two experiments illustrate that compound splitting is beneficial for the bilingual term lexicon acquisition task.; Le nombre de termes spécialisés croît constamment dans les documents, à un rythme difficile à suivre pour les organismes de normalisation de la terminologie. Les méthodes de construction des lexiques terminologiques bilingues à partir de corpus de textes proposent des solutions. Notre thèse s'inscrit dans cette problématique : la construction de lexiques bilingues à partir de corpus comparables.Les termes composés (les termes contenant plusieurs radicaux, mais un seul mot graphique) constituent un défi pour les applications du traitement automatique des langues. Étant donné leur forme graphique, ils sont souvent traités comme des termes simples, ce qui empêche de capturer leur complexité sémantique. Notre participation à une évaluation d'extraction automatique de termes a permis de vérifier notre hypothèse : les termes composés nécessitent un traitement particulier dans un contexte multilingue. Nous avons proposé une méthode de reconnaissance et de segmentation des termes composés, combinant des caractéristiques dépendantes et indépendantes de la langue. Elle permet d'obtenir des résultats comparables à ceux des méthodes de l'état de l'art, tout en étant validée sur un échantillon de familles de langues varié (germanique, slave, romane) et adaptable au domaine de spécialité (vérifiée sur deux domaines : l'énergie éolienne et le cancer du sein).Nous avons exploité les segmentations produites pour la traduction compositionnelle des termes et pour la détection des variantes syntagmatiques des termes composés dans les textes spécialisés. Ces deux expériences illustrent l'utilité de la segmentation pour la construction des lexiques terminologiques bilingues.

The number of specialized terms continuously grows in the documents, at a pace which is difficult to follow for the terminology standardization organizations. The methods of bilingual term lexicon construction from the text corpora provide solutions. Our thesis falls into this topic: bilingual lexicon acquisition from comparable corpora. Compound terms (terms containing several roots, but a single graphical unit) are challenging for natural language processing applications. Given their graphical form, they are often handled in the same manner as single word terms, which prevents from apprehending their semantic complexity. Our involvement in an automatical terminology extraction evaluation allowed us to check our hypothesis: compound terms need a particular processing in a multilingual context.We proposed a method for compound terms recognition and splitting, which combines language-independent and language-specific features. It allowed us to obtain results comparable with those of state-of-the-art methods, while validating on a sample of languages from several families (germanic, slavic, romance languages), and adapting the method to specialized domains (tested on two domains: wind energy and breast cancer). We used the produced segmentations for compositional translation of compound terms, and for their multi-word variant recognition in the specialized texts. These two experiments illustrate that compound splitting is beneficial for the bilingual term lexicon acquisition task.; Le nombre de termes spécialisés croît constamment dans les documents, à un rythme difficile à suivre pour les organismes de normalisation de la terminologie. Les méthodes de construction des lexiques terminologiques bilingues à partir de corpus de textes proposent des solutions. Notre thèse s'inscrit dans cette problématique : la construction de lexiques bilingues à partir de corpus comparables.Les termes composés (les termes contenant plusieurs radicaux, mais un seul mot graphique) constituent un défi pour les applications du traitement automatique des langues. Étant donné leur forme graphique, ils sont souvent traités comme des termes simples, ce qui empêche de capturer leur complexité sémantique. Notre participation à une évaluation d'extraction automatique de termes a permis de vérifier notre hypothèse : les termes composés nécessitent un traitement particulier dans un contexte multilingue. Nous avons proposé une méthode de reconnaissance et de segmentation des termes composés, combinant des caractéristiques dépendantes et indépendantes de la langue. Elle permet d'obtenir des résultats comparables à ceux des méthodes de l'état de l'art, tout en étant validée sur un échantillon de familles de langues varié (germanique, slave, romane) et adaptable au domaine de spécialité (vérifiée sur deux domaines : l'énergie éolienne et le cancer du sein).Nous avons exploité les segmentations produites pour la traduction compositionnelle des termes et pour la détection des variantes syntagmatiques des termes composés dans les textes spécialisés. Ces deux expériences illustrent l'utilité de la segmentation pour la construction des lexiques terminologiques bilingues.

Conference paper We propose and evaluate the task of technology term recognition: a method to extract technology terms at a synchronic level from a corpus of scientific publications. The proposed method is built on the principles of terminology extraction and distributional semantics. It is realized as a regression task in a vector space model. In this method, candidate terms are first extracted from text. Subsequently, using the random indexing technique, the extracted candidate terms are represented as vectors in a Euclidean vector space of reduced dimensionality. These vectors are derived from the frequency of co-occurrences of candidate terms and words in windows of text surrounding candidate terms in the input corpus (context window). The constructed vector space and a set of manually tagged technology terms (reference vectors) in a k-nearest neighbours regression framework is then used to identify terms that signify technology concepts. We examine a number of factors that play roles in the performance of the proposed method, i.e. the configuration of context windows, neighborhood size (k) selection, and reference vector size. peer-reviewed

In this paper a method and a flexible tool for performing monolingual term extraction is presented; based on the use of syntactic analysis where information on parts-of-speech; syntactic functions and surface syntax tags can be utilised. The standard approaches to evaluating term extraction; namely by manual evaluation of the top n term candidates or by comparing to a gold standard consisting of a list of terms from a specific domain can have its advantages; but in this paper we try to realise a proposal by Bernier-Colborne (2012) where extracted terms are compared to a gold standard consisting of a test corpus where terms have been annotated in context. Apart from applying this evaluation to different configuratio

Ce travail porte sur la construction d’un corpus étalon pour l’évaluation automatisée des extracteurs de termes. Ces programmes informatiques, conçus pour extraire automatiquement les termes contenus dans un corpus, sont utilisés dans différentes applications, telles que la terminographie, la traduction, la recherche d’information, l’indexation, etc. Ainsi, leur évaluation doit être faite en fonction d’une application précise. Une façon d’évaluer les extracteurs consiste à annoter toutes les occurrences des termes dans un corpus, ce qui nécessite un protocole de repérage et de découpage des unités terminologiques. À notre connaissance, il n’existe pas de corpus annoté bien documenté pour l’évaluation des extracteurs. Ce travail vise à construire un tel corpus et à décrire les problèmes qui doivent être abordés pour y parvenir. Le corpus étalon que nous proposons est un corpus entièrement annoté, construit en fonction d’une application précise, à savoir la compilation d’un dictionnaire spécialisé de la mécanique automobile. Ce corpus rend compte de la variété des réalisations des termes en contexte. Les termes sont sélectionnés en fonction de critères précis liés à l’application, ainsi qu’à certaines propriétés formelles, linguistiques et conceptuelles des termes et des variantes terminologiques. Pour évaluer un extracteur au moyen de ce corpus, il suffit d’extraire toutes les unités terminologiques du corpus et de comparer, au moyen de métriques, cette liste à la sortie de l’extracteur. On peut aussi créer une liste de référence sur mesure en extrayant des sous-ensembles de termes en fonction de différents critères. Ce travail permet une évaluation automatique des extracteurs qui tient compte du rôle de l’application. Cette évaluation étant reproductible, elle peut servir non seulement à mesurer la qualité d’un extracteur, mais à comparer différents extracteurs et à améliorer les techniques d’extraction., We describe a methodology for constructing a gold standard for the automatic evaluation of term extractors. These programs, designed to automatically extract specialized terms from a corpus, are used in various settings, including terminology work, translation, information retrieval, indexing, etc. Thus, the evaluation of term extractors must be carried out in accordance with a specific application. One way of evaluating term extractors is to construct a corpus in which all term occurrences have been annotated. This involves establishing a protocol for term selection and term boundary identification. To our knowledge, no well-documented annotated corpus is available for the evaluation of term extractors. This contribution aims to build such a corpus and describe what issues must be dealt with in the process. The gold standard we propose is a fully annotated corpus, constructed in accordance with a specific terminological setting, namely the compilation of a specialized dictionary of automotive mechanics. This annotated corpus accounts for the wide variety of realizations of terms in context. Terms are selected in accordance with specific criteria pertaining to the terminological setting as well as formal, linguistic and conceptual properties of terms and term variations. To evaluate a term extractor, a list of all the terminological units in the corpus is extracted and compared to the output of the term extractor, using a set of metrics to assess its performance. Subsets of terminological units may also be extracted, providing a level of customization. This allows an automatic and application-driven evaluation of term extractors. Due to its reusability, it can serve not only to assess the performance of a particular extractor, but also to compare different extractors and fine-tune extraction techniques.

Terminologies are becoming more important to modern day society as technology and science continue to grow at an accelerating rate in a globalized environment. Agreeing upon which terms should be used to represent which concepts and how those terms should be translated into different languages is important if we wish to be able to communicate with as little confusion and misunderstandings as possible. Since the 1990s, an increasing amount of terminology research has been devoted to facilitating and augmenting terminology-related tasks by using computers and computational methods. One focus for this research is Automatic Term Extraction (ATE). In this compilation thesis, studies on both bilingual and monolingual ATE are presented. First, two publications reporting on how bilingual ATE using the align-extract approach can be used to extract patent terms. The result in this case was 181,000 manually validated English-Swedish patent terms which were to be used in a machine translation system for patent documents. A critical component of the method used is the Q-value metric, presented in the third paper, which can be used to rank extracted term candidates (TC) in an order that correlates with TC precision. The use of Machine Learning (ML) in monolingual ATE is the topic of the two final contributions. The first ML-related publication shows that rule induction based ML can be used to generate linguistic term selection patterns, and in the second ML-related publication, contrastive n-gram language models are used in conjunction with SVM ML to improve the precision of term candidates selected using linguistic patterns.

The objective of the OSCB multilingual terminology work package (WP4) is to compile a database of English, Dutch and French terminology related to the domains that will be covered in the OSCB project (e.g. cultural events). The development process of this termbase will be based on the methodological guidelines set forth in the termontography methodological framework (Temmerman & Kerremans 2003; Kerremans e.a. 2005; Temmerman e.a. 2006). Termontography is an application- or task-oriented approach for terminology description. An important view in this approach is that a knowledge analysis phase should ideally precede the methodological steps which are generally conceived as the starting-points in terminography: i.e. the compilation of a domain-specific corpus of texts (Moreno & Perez 2001) and the understanding and analysis of the categories that occur in a certain domain (Meyer e.a. 1997. This view results from the fact that terminological databases need to represent in natural language those items of knowledge or 'units of understanding' (Temmerman 2000) which are considered relevant to specific purposes, applications or groups of users (Aussenac-Gilles e.a. 2002). The methodology is supported by a suite of software tools (i.e. the Termontography Workbench) that allows specialised texts (irrespective of the language) to be analysed manually following the methodological guidelines (De Baer e.a. 2008). This report will focus on recent trends in the (semi-)automatic compilation of multilingual termbases. Two areas will be explored: * Computational terminology, a research area which is gaining more interest due to its importance for terminology work or in areas such as knowledge management, text mining, information retrieval and extraction or ontology development (Bourigault e.a. 2001). It will be examined to what extent the OSCB multilingual termbase can benefit from recent trends in the area of computational terminology. The chapter will focus on recent work related to automatic extraction of terminological data (e.g. terms, semantic relations, definitions, translations) and, in this way, will present possibilities for (semi-)automatically developing the OSCB termbase. * Open linguistics, a recently coined term to denote a subdiscipline of linguistics that is devoted to research on different aspects of open linguistic data. More information on this new research area can be found on: http://linguistics.okfn.org/. As the multilingual termbase is going to be part of the OSCB framework for Linked Data, it will also be examined how it can benefit from or relate to important initiatives (e.g. projects, software tools, language resources, guidelines) with respect to open linguistic data. This chapter will provide a summary of some of these important initiatives in the area of open linguistics. On the basis of a description of state-of-the-art work in computational terminology and open linguistics, the following issues will be addressed in this report: * What recent trends can be observed with respectto the automatic extraction of terminological data and (how) can these trends contribute to a further refinement of the termontography method (Temmerman & Kerremans 2003; Kerremans e.a. 2005; Temmerman e.a. 2006) and tools (De Baer e.a. 2008)? * How can the OSCB project - and more specifically the multilingual terminology work package - benefit from initiatives related to open linguistic data? For instance, what open linguistic data could be deployed for the compilation the OSCB termbase? In what formats should we publish the multilingual terminological data? What methods could be used for linking or aligning terminological data? Etc. We will first discuss some important shifts in the field of terminology and explain how these shifts have influenced the way many multilingual termbases are used and compiled today. Next, we will explore some of the recent methods in automatic extraction of terminological data. Then, we will summarise some important initiatives with respect to open linguistic data, such as available language resources, exchange formats or methods for linking terminological data. Finally, we will summarise the most important trends and discuss how they can be adopted in the OSCB project for the compilation of the multilingual termbase.

A common framework under which the various studies on terminology processing can be viewed is to consider not only the texts from which the terminological resources are built but particularly the applications targeted. The current book, first published as a Special Issue of Terminology 11:1 (2005), analyses the influence of applications on term definition and processing. Two types of applications have been identified: intermediary and terminal applications (involving end users). Intermediary applications concern the building of terminological knowledge resources such as domain-specific dictionaries, ontologies, thesaurus or taxonomies. These knowledge resources then form the inputs to terminal applications such as information extraction, information retrieval, science and technology watch or automated book index building. Most of the applications dealt with in the book fall into the first category. This book represents the first attempt, from a pluridisciplinary viewpoint, to take into account the role of applications in the processing of terminology.

U članku se govori o četiri načina formiranja ortografije osnovnoga oblika anglicizama u ruskoj računalnoj terminologiji. Analiza je provedena prema teoretskim i metodološkim principima proučavanja jezičnih dodira Rudolfa Filipovića. Budući da se analiziraju anglicizmi u ruskom, zbog specifičnosti ruskoga fonetskog sustava, uvodi se i peti oblik adaptacije anglicizma na ortografskoj razini. Ortografija osnovnog oblika anglicizma može se formirati na pet načina: prema ortografiji i izgovorumodela, njihovoj kombinaciji, utjecaju jezika posrednika i s obzirom na izgovor palataliziranih suglasnika. U analizi i klasifikaciji ortografije računalnih anglicizama u ruskom jeziku, korišteni su indeksi kojima je u Rječniku anglicizama u hrvatskom ili srpskom jeziku Rudolf Filipović označavao ortografiju osnovnih oblika anglicizama: 1.) indeks a koji predstavlja formiranje osnovnog oblika anglicizma prema izgovoru modela; 2.) indeks b – osnovni se oblik formira prema ortografiji modela; 3.) indeks c – osnovni se oblik formira kombinacijom izgovora i ortografije; 4.) indeks d – osnovni se oblik formira pod utjecajem jezika posrednika te 5.) indeks e - osnovni se oblik formira prema izgovoru palataliziranih suglasnika. Zbog nesređene situacije u ovom dijelu leksika zamjetna je varijabilnost, tj. preinačivanje termina., The paper presents the results of the analysis of the orthography of the basic form of Russian computational terminology anglicisms. Their adaptation is represented by five indices: a) according to the pronunciation of the model, b) according to the orthography of the model, c) according to the combination of pronunciation and orthography of the model, d) according to an intermediary language and e) according to Russian palatalized consonants. Due to the contemporary and continual process of huge lexical entry, the presence of variability of computational anglicisms in the Russian language is evident.

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