A Cross-Lingual Similarity Measure for Detecting Biomedical Term Translations

Bilingual dictionaries for technical terms such as biomedical terms are an important resource for machine translation systems as well as for humans who would like to understand a concept described in a foreign language. Often a biomedical term is first proposed in English and later it is manually translated to other languages. Despite the fact that there are large monolingual lexicons of biomedical terms, only a fraction of those term lexicons are translated to other languages. Manually compiling large-scale bilingual dictionaries for technical domains is a challenging task because it is difficult to find a sufficiently large number of bilingual experts. We propose a cross-lingual similarity measure for detecting most similar translation candidates for a biomedical term specified in one language (source) from another language (target). Specifically, a biomedical term in a language is represented using two types of features: (a) intrinsic features that consist of character n-grams extracted from the term under consideration, and (b) extrinsic features that consist of unigrams and bigrams extracted from the contextual windows surrounding the term under consideration. We propose a cross-lingual similarity measure using each of those feature types. First, to reduce the dimensionality of the feature space in each language, we propose prototype vector projection (PVP)—a non-negative lower-dimensional vector projection method. Second, we propose a method to learn a mapping between the feature spaces in the source and target language using partial least squares regression (PLSR). The proposed method requires only a small number of training instances to learn a cross-lingual similarity measure. The proposed PVP method outperforms popular dimensionality reduction methods such as the singular value decomposition (SVD) and non-negative matrix factorization (NMF) in a nearest neighbor prediction task. Moreover, our experimental results covering several language pairs such as English–French, English–Spanish, English–Greek, and English–Japanese show that the proposed method outperforms several other feature projection methods in biomedical term translation prediction tasks

A Survey of Paraphrasing and Textual Entailment Methods

Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.Comment: Technical Report, Natural Language Processing Group, Department of Informatics, Athens University of Economics and Business, Greece, 201

Entry Generation for New Words by Analogy for Morphological Lexicons

Peer reviewe

El tratamiento y la representación de las colocaciones verbales en el lenguaje especializado del turismo de aventura

A collocation is considered a frequent co-occurrence of two words which hold a syntactic relationship and whose elements enjoy a different status. Given their perception as a unit in language, access to the prominent word (base) involves immediate access to the other item (collocate). In terms of meaning, some combinations tend to be more transparent than others. The pervasiveness of these word associations in language has sparked a strong research interest in the last decades. A compelling reason for this approach may be the fact that they are naturally produced by native speakers but must be actively learned by non-native individuals. Not only has this reality led to their treatment in the general language, but it has also become a legitimate field of study in a wide range of specialized languages, such as the environment, computing, law or tourism, which is our object of study. As a consequence, specialized knowledge resources covering this type of word combinations have seen the light with the primary purpose of offering some extra help to people who deal with this type of language, for example, translators, linguists or other professionals. Nevertheless, there is still much to do in this respect. Taken this into account, it is hypothesized that verb collocations in the specialized language of adventure tourism convey specialized meaning that is worth being collected in terminological products. Therefore, this work endeavors, as its main purpose, to perform a deep analysis of verb collocations in this specialized domain and their implementation in the entries for motion verbs in DicoAdventure, a specialized dictionary of adventure tourism, whose inspirational idea was to highlight the significant role of verbs in the linguistic expression of concepts. Accordingly, the following theoretical objectives were set: first, to cover the linguistic branches which influence specialized lexicography; second, to define the concept of specialized collocation; and third, to examine a vast number of lexicographical and terminological resources so as to discover the items of information that would make an adequate representation of collocations in a specialized dictionary and, then, design a model for such task. Furthermore, the following practical objectives were formulated: first, to extract the motion verbs which would be the bases of the collocations implemented; second, to retrieve the lexical collocations of these verbs; and third, to classify the resulting list of collocations according to the meaning expressed, that is, actual motion or fictive (or metaphorical) motion. The practical steps taken in this research were based on the English monolingual specialized corpus ADVENCOR, which contains promotional texts about adventure tourism, and the use of corpus management software. The results of the theoretical work can be summarized as follows: (1) the specialized language of adventure tourism must be considered as specialized as any others; (2) collocations are not usually encoded in verb entries in dictionaries; and (3) a specialized collocation carries specialized knowledge which must be covered in terminological products. On the other hand, regarding the practical work, 12% of the verbs extracted were selected, as they were the ones expressing motion. However, only 46.61% of them produced collocations according to the extraction criteria established. Last, after applying more strict criteria for the collocation classification, only 25.42% of the verbs along with their collocations were collected in the dictionary. In addition to these results, the theory of Frame Semantics proved useful to understand the meaning of the verbs and their collocates. As for their implementation, which was the primary objective of this doctoral dissertation, the inclusion of verb collocations was of paramount importance for the identification of distinct meanings expressed by one verb in different contexts, as collocates conveyed subtle nuances of meaning. Finally, it was concluded that the incorporation of explanations about the combinations in lay terms facilitates the comprehension of the entries to any type of user, from experts to laypersons, which makes DicoAdventure a terminological product that can render valuable assistance to individuals with distinct specialized expertise.Una colocación es una coaparición frecuente de dos palabras que mantienen una relación sintáctica y cuyos elementos alcanzan un estatus diferente. Puesto que se perciben como una unidad del lenguaje, el acceso al elemento prominente (base) conlleva el acceso inmediato al otro componente (colocativo). Con respecto a su significado, algunas combinaciones tienden a ser más transparentes que otras. La constante presencia de las colocaciones en el lenguaje ha despertado gran interés por su investigación en las últimas décadas. Una razón convincente de este acercamiento podría ser el hecho de que los hablantes nativos las producen de forma natural, mientras que los no nativos deben aprenderlas de manera activa. Esta realidad no solo ha llevado a su tratamiento en el lenguaje general, sino también a que se hayan convertido en un campo de estudio legítimo en una amplia gama de lenguajes especializados, como son el medio ambiente, la informática, el derecho o el turismo, que es el objeto de estudio de esta investigación. Como consecuencia, se han creado recursos de conocimiento especializado con el propósito fundamental de ofrecer ayuda a las personas que interactúan con este tipo de lenguaje, por ejemplo, traductores, lingüistas u otro tipo de profesionales. No obstante, aún queda mucho por hacer en este aspecto. Teniendo esto en cuenta, la hipótesis de este trabajo se basa en la idea de que las colocaciones verbales en el lenguaje especializado del turismo de aventura expresan significados especializados que merecen ser recopilados en productos terminológicos. Por lo tanto, este trabajo tiene como principal objetivo el estudio exhaustivo de las colocaciones verbales en este campo de especialidad y su implementación en las entradas de los verbos de movimiento en DicoAdventure, un diccionario especializado del turismo de aventura, cuyo punto de partida fue la intención de destacar el importante papel que juegan los verbos en la expresión lingüística de los conceptos. Por consiguiente, se establecieron los siguientes objetivos teóricos: primero, revisar las ramas de la lingüística que ejercen una influencia en la lexicografía especializada; segundo, definir el concepto de colocación especializada; y tercero, examinar un gran número de recursos lexicográficos y terminológicos para descubrir qué tipo de información conformaría una representación adecuada de colocaciones en un diccionario especializado y, a continuación, diseñar un modelo para esta tarea. Además, se propusieron estos objetivos prácticos: primero, extraer los verbos de movimiento que serían las bases de las colocaciones implementadas; segundo, extraer las colocaciones léxicas de estos verbos; y tercero; clasificar la lista resultante de colocaciones según su significado, es decir, movimiento real o movimiento figurado (o metafórico). Los pasos prácticos que se dieron en esta investigación se llevaron a cabo mediante la gestión del corpus especializado monolingüe en inglés ADVENCOR, que contiene textos promocionales sobre el turismo de aventura, y el uso de software de gestión de corpus. Los resultados de la parte teórica del trabajo se pueden resumir de la siguiente manera: (1) el lenguaje especializado del turismo de aventura debe considerarse tan especializado como otros; (2) las colocaciones no suelen codificarse en las entradas de verbos en los diccionarios; y (3) una colocación especializada contiene conocimiento especializado que debe aparecer en productos terminológicos. Por otro lado, con respecto al trabajo práctico, se seleccionó el 12% de los verbos extraídos, ya que eran los que expresaban movimiento. Sin embargo, solo el 46,61% de ellos produjeron colocaciones según los criterios de extracción establecidos. Por último, después de aplicar criterios más estrictos para la clasificación de las colocaciones, solo el 25,42% de los verbos con sus colocaciones fueron recogidos en el diccionario. Además de estos resultados, se demostró la utilidad de la teoría de la Semántica de Marcos para entender el significado de los verbos y sus colocativos. En cuanto a su implementación, que era el objetivo principal de esta tesis doctoral, la inclusión de colocaciones verbales fue de suma importancia para la identificación de los distintos significados expresados por un verbo en diferentes contextos, puesto que los colocativos aportaban sutiles matices de significado. Finalmente, se concluyó que la incorporación de explicaciones sobre las combinaciones en términos legos favorece la comprensión de las entradas por parte de cualquier tipo de usuario, desde expertos a personas no especialistas, lo cual hace de DicoAdventure un producto terminológico que puede proporcionar valiosa ayuda a personas con diversa formación especializada

AXEL: A framework to deal with ambiguity in three-noun compounds

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 6/12/2010.Cognitive Linguistics has been widely used to deal with the ambiguity generated by words in combination. Although this domain offers many solutions to address this challenge, not all of them can be implemented in a computational environment. The Dynamic Construal of Meaning framework is argued to have this ability because it describes an intrinsic degree of association of meanings, which in turn, can be translated into computational programs. A limitation towards a computational approach, however, has been the lack of syntactic parameters. This research argues that this limitation could be overcome with the aid of the Generative Lexicon Theory (GLT). Specifically, this dissertation formulated possible means to marry the GLT and Cognitive Linguistics in a novel rapprochement between the two. This bond between opposing theories provided the means to design a computational template (the AXEL System) by realising syntax and semantics at software levels. An instance of the AXEL system was created using a Design Research approach. Planned iterations were involved in the development to improve artefact performance. Such iterations boosted performance-improving, which accounted for the degree of association of meanings in three-noun compounds. This dissertation delivered three major contributions on the brink of a so-called turning point in Computational Linguistics (CL). First, the AXEL system was used to disclose hidden lexical patterns on ambiguity. These patterns are difficult, if not impossible, to be identified without automatic techniques. This research claimed that these patterns can assist audiences of linguists to review lexical knowledge on a software-based viewpoint. Following linguistic awareness, the second result advocated for the adoption of improved resources by decreasing electronic space of Sense Enumerative Lexicons (SELs). The AXEL system deployed the generation of “at the moment of use” interpretations, optimising the way the space is needed for lexical storage. Finally, this research introduced a subsystem of metrics to characterise an ambiguous degree of association of three-noun compounds enabling ranking methods. Weighing methods delivered mechanisms of classification of meanings towards Word Sense Disambiguation (WSD). Overall these results attempted to tackle difficulties in understanding studies of Lexical Semantics via software tools

Investigating Frequency and Type of Lexical Collocations in Applied Linguistics Journal Articles Written in English by Iranian and Norwegian Scholars

Master's thesis in Literacy StudiesIn today’s academic world, the research interest in corpus linguistics has shifted towards word co-occurrence rather than single words. Accordingly, a great body of literature has been devoted to investigations of recurrent word combinations in academic prose using frequency and dispersion parameters. This has resulted in analysis of corpus in different fields of study to collect comprehensive lists of academic collocations. Moreover, many contrastive studies have been conducted to compare the collocations used by native and non-native speakers of English. However, to the author’s knowledge, few studies have been conducted to compare the most frequent collocations in two corpora of research articles written by non-native speakers of English published in international journals in the field of applied linguistics. To fill this gap in the literature, the current study investigated the most frequent collocations used by Iranian and Norwegian scholars in a corpus of 17 articles published in the Journal of Pragmatics through a frequency-based approach. Nine out of 17 articles were written by Iranian scholars including 67,673 words and eight out of 17 articles were written by Norwegian scholars comprising of 64,682 words. The data of this study were collected using Collocation Extract software. The results of the study were presented in three phases. In the first phase, 15 most frequent lexical collocations in both corpora were identified which were classified under three types of lexical collocations. Based on what was obtained, Adj+N collocation type had the most proportion in the corpora while Adv+Adj type had the least proportion. In the second phase, the lexical collocations of the Iranian corpus were presented including a total of 818 collocations classified under five types. According to the results, Adj+N was the most frequent type while N+V was the least frequent one. Similar to the Iranian corpus, lexical collocations of the Norwegian corpus were identified. They were classified under four types including a total of 462, among which Adj+N was the most frequent type while Adv+Adj was the least frequent one. In the third phase, frequencies of lexical collocations were compared in the two corpora. According to the obtained results, the two corpora did not have any had significant difference in the use of all types of collocation except for Adj+N type of lexical collocations

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018 : 10-12 December 2018, Torino

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

SEMANTIQUE DISTRIBUTIONNELLE

This special issue contains state-of-the-art papers on distributional semantic

Students´ language in computer-assisted tutoring of mathematical proofs

Truth and proof are central to mathematics. Proving (or disproving) seemingly simple statements often turns out to be one of the hardest mathematical tasks. Yet, doing proofs is rarely taught in the classroom. Studies on cognitive difficulties in learning to do proofs have shown that pupils and students not only often do not understand or cannot apply basic formal reasoning techniques and do not know how to use formal mathematical language, but, at a far more fundamental level, they also do not understand what it means to prove a statement or even do not see the purpose of proof at all. Since insight into the importance of proof and doing proofs as such cannot be learnt other than by practice, learning support through individualised tutoring is in demand. This volume presents a part of an interdisciplinary project, set at the intersection of pedagogical science, artificial intelligence, and (computational) linguistics, which investigated issues involved in provisioning computer-based tutoring of mathematical proofs through dialogue in natural language. The ultimate goal in this context, addressing the above-mentioned need for learning support, is to build intelligent automated tutoring systems for mathematical proofs. The research presented here has been focused on the language that students use while interacting with such a system: its linguistic propeties and computational modelling. Contribution is made at three levels: first, an analysis of language phenomena found in students´ input to a (simulated) proof tutoring system is conducted and the variety of students´ verbalisations is quantitatively assessed, second, a general computational processing strategy for informal mathematical language and methods of modelling prominent language phenomena are proposed, and third, the prospects for natural language as an input modality for proof tutoring systems is evaluated based on collected corpora