842 resultados para Word Sense Disambiguation
Resumo:
En este trabajo presentamos unos resultados preliminares obtenidos mediante la aplicación de una nueva técnica de construcción de grafos semánticos a la tarea de desambiguación del sentido de las palabras en un entorno multilingüe. Gracias al uso de esta técnica no supervisada, inducimos los sentidos asociados a las traducciones de la palabra ambigua considerada en la lengua destino. Utilizamos las traducciones de las palabras del contexto de la palabra ambigua en la lengua origen para seleccionar el sentido más probable de la traducción. El sistema ha sido evaluado sobre la colección de datos de una tarea de desambiguación multilingüe que se propuso en la competición SemEval-2010, consiguiendo superar los resultados de todos los sistemas no supervisados que participaron en aquella tarea.
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In this work we present a semantic framework suitable of being used as support tool for recommender systems. Our purpose is to use the semantic information provided by a set of integrated resources to enrich texts by conducting different NLP tasks: WSD, domain classification, semantic similarities and sentiment analysis. After obtaining the textual semantic enrichment we would be able to recommend similar content or even to rate texts according to different dimensions. First of all, we describe the main characteristics of the semantic integrated resources with an exhaustive evaluation. Next, we demonstrate the usefulness of our resource in different NLP tasks and campaigns. Moreover, we present a combination of different NLP approaches that provide enough knowledge for being used as support tool for recommender systems. Finally, we illustrate a case of study with information related to movies and TV series to demonstrate that our framework works properly.
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Yorick Wilks is a central figure in the fields of Natural Language Processing and Artificial Intelligence. His influence extends to many areas and includes contributions to Machines Translation, word sense disambiguation, dialogue modeling and Information Extraction. This book celebrates the work of Yorick Wilks in the form of a selection of his papers which are intended to reflect the range and depth of his work. The volume accompanies a Festschrift which celebrates his contribution to the fields of Computational Linguistics and Artificial Intelligence. The papers include early work carried out at Cambridge University, descriptions of groundbreaking work on Machine Translation and Preference Semantics as well as more recent works on belief modeling and computational semantics. The selected papers reflect Yorick’s contribution to both practical and theoretical aspects of automatic language processing.
Resumo:
Yorick Wilks is a central figure in the fields of Natural Language Processing and Artificial Intelligence. His influence has extends to many areas of these fields and includes contributions to Machine Translation, word sense disambiguation, dialogue modeling and Information Extraction.This book celebrates the work of Yorick Wilks from the perspective of his peers. It consists of original chapters each of which analyses an aspect of his work and links it to current thinking in that area. His work has spanned over four decades but is shown to be pertinent to recent developments in language processing such as the Semantic Web.This volume forms a two-part set together with Words and Intelligence I, Selected Works by Yorick Wilks, by the same editors.
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This paper presents an approach for assisting low-literacy readers in accessing Web online information. The oEducational FACILITAo tool is a Web content adaptation tool that provides innovative features and follows more intuitive interaction models regarding accessibility concerns. Especially, we propose an interaction model and a Web application that explore the natural language processing tasks of lexical elaboration and named entity labeling for improving Web accessibility. We report on the results obtained from a pilot study on usability analysis carried out with low-literacy users. The preliminary results show that oEducational FACILITAo improves the comprehension of text elements, although the assistance mechanisms might also confuse users when word sense ambiguity is introduced, by gathering, for a complex word, a list of synonyms with multiple meanings. This fact evokes a future solution in which the correct sense for a complex word in a sentence is identified, solving this pervasive characteristic of natural languages. The pilot study also identified that experienced computer users find the tool to be more useful than novice computer users do.
Resumo:
In this action research study of my classroom of sixth grade mathematics, I investigated word problems. I discovered that my students did not like to try word problems because they did not understand what was being asked of them. My students also saw no reason for solving word problems or in having the ability to solve them. I used word problems that covered topics that were familiar to the students and that covered the skills necessary at the sixth grade level. I wanted to deepen their understanding of math and its importance. By having my students journal to me about the steps that they had taken along the way to solve the word problem I was able to see where confusion occurred. Consequently I was able to help clarify where my students made mistakes. Also, through writing down the steps taken, students did see more clearly where their errors took place. Each time that my students wrote their explanations to the steps that they used in solving the word problems they did solved them more easily. As I observed my students they took more time in writing their explanations and did not look at it as such a difficult task anymore.
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"First published in the Christian herald."
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"First published in the Christian herald."
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A distinct metonymic pattern was discovered in the course of conducting a corpus-based study of figurative uses of WORD. The pattern involved examples such as Not one word of it made any sense and I agree with every word. It was labelled ‘hyperbolic synecdoche’, defined as a case in which a lexeme which typically refers to part of an entity (a) is used to stand for the whole entity and (b) is described with reference to the end point on a scale. Specifically, the speaker/writer selects the perspective of a lower-level unit (such as word for ‘utterance’), which is quantified as NOTHING or ALL, thus forming a subset of ‘extreme case formulations’. Hyperbolic synecdoche was found to exhibit a restricted range of lexicogrammatical patterns involving word, with the negated NOTHING patterns being considerably more common than the ALL patterns. The phenomenon was shown to be common in metonymic uses in general, constituting one-fifth of all cases of metonymy in word. The examples of hyperbolic synecdoche were found not to be covered by the oftquoted ‘abbreviation’ rationale for metonymy; instead, they represent a more roundabout way of expression. It is shown that other cases of hyperbolic synecdoche exist outside of word and the domain of communication (such as ‘time’ and ‘money’).
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Altruism is a deep and complex phenomenon that is analysed by scholars of various disciplines, including psychology, philosophy, biology, evolutionary anthropology and experimental economics. Much confusion arises in current literature because the term altruism covers variable concepts and processes across disciplines. Here we investigate the sense given to altruism when used in different fields and argumentative contexts. We argue that four distinct but related concepts need to be distinguished: (a) psychological altruism, the genuine motivation to improve others' interests and welfare; (b) reproductive altruism, which involves increasing others' chances of survival and reproduction at the actor's expense; (c) behavioural altruism, which involves bearing some cost in the interest of others; and (d) preference altruism, which is a preference for others' interests. We show how this conceptual clarification permits the identification of overstated claims that stem from an imprecise use of terminology. Distinguishing these four types of altruism will help to solve rhetorical conflicts that currently undermine the interdisciplinary debate about human altruism.
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In natural languages with a high degree of word-order freedom syntactic phenomena like dependencies (subordinations) or valencies do not depend on the word-order (or on the individual positions of the individual words). This means that some permutations of sentences of these languages are in some (important) sense syntactically equivalent. Here we study this phenomenon in a formal way. Various types of j-monotonicity for restarting automata can serve as parameters for the degree of word-order freedom and for the complexity of word-order in sentences (languages). Here we combine two types of parameters on computations of restarting automata: 1. the degree of j-monotonicity, and 2. the number of rewrites per cycle. We study these notions formally in order to obtain an adequate tool for modelling and comparing formal descriptions of (natural) languages with different degrees of word-order freedom and word-order complexity.
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Given the paucity of research in this area, the primary aim of this study was to explore how parents of infants with unclear sex at birth made sense of 'intersex'. Qualitative methods were, used (semi-structured interviews, interpretative phenomenological analysis) with 10 parents to generate pertinent themes and provide ideas for further research. Our analysis highlights the fundamental shock engendered by the uncertain sex status of children, and documents parental struggles to negotiate a coherent sex identity for their children. Findings are discussed in light of the rigid two-sex system which pervades medicine and everyday life, and we argue that greater understanding of the complexity of sex and gender is required in order to facilitate better service provision and, ultimately, greater informed consent and parental participation regarding decisions about their children's status.
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Tai languages are often described as “lacking” a major lexical class “adjectives”; accordingly, they and other area languages are frequently cited as evidence against adjectival universality. This article brings the putative lack under examination, arguing that a more complete distributional analysis reveals a pattern: overlap is highest among semantically peripheral adjectives and verbs and in constructions prototypically associated to both classes crosslinguistically, and lowest among semantically core adjectives and verbs and in constructions prototypically associated to only one or the other class. Rather than “lacking” adjectives, data from Thai thus in fact support functional-typological characterizations of adjectival universality such as those of Givón (1984), Croft (2001), and Dixon (2004). Finally, while data from Thai would fail to falsify an adaptation of Enfield's (2004) Lao lexical class-taxonomy (in which adjectives are treated as a verbal subclass) on its own terms, this article argues that in absence of both universally-applicable criteria for the evaluation of categorial taxonomies crosslinguistically and evidence for the cognitive reality of categorial taxonomies so stipulated, even this more limited sense of a “lack” of adjectives in Thai is less radical a challenge to adjectival universality than has sometimes been supposed.
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Derivational morphology proposes meaningful connections between words and is largely unrepresented in lexical databases. This thesis presents a project to enrich a lexical database with morphological links and to evaluate their contribution to disambiguation. A lexical database with sense distinctions was required. WordNet was chosen because of its free availability and widespread use. Its suitability was assessed through critical evaluation with respect to specifications and criticisms, using a transparent, extensible model. The identification of serious shortcomings suggested a portable enrichment methodology, applicable to alternative resources. Although 40% of the most frequent words are prepositions, they have been largely ignored by computational linguists, so addition of prepositions was also required. The preferred approach to morphological enrichment was to infer relations from phenomena discovered algorithmically. Both existing databases and existing algorithms can capture regular morphological relations, but cannot capture exceptions correctly; neither of them provide any semantic information. Some morphological analysis algorithms are subject to the fallacy that morphological analysis can be performed simply by segmentation. Morphological rules, grounded in observation and etymology, govern associations between and attachment of suffixes and contribute to defining the meaning of morphological relationships. Specifying character substitutions circumvents the segmentation fallacy. Morphological rules are prone to undergeneration, minimised through a variable lexical validity requirement, and overgeneration, minimised by rule reformulation and restricting monosyllabic output. Rules take into account the morphology of ancestor languages through co-occurrences of morphological patterns. Multiple rules applicable to an input suffix need their precedence established. The resistance of prefixations to segmentation has been addressed by identifying linking vowel exceptions and irregular prefixes. The automatic affix discovery algorithm applies heuristics to identify meaningful affixes and is combined with morphological rules into a hybrid model, fed only with empirical data, collected without supervision. Further algorithms apply the rules optimally to automatically pre-identified suffixes and break words into their component morphemes. To handle exceptions, stoplists were created in response to initial errors and fed back into the model through iterative development, leading to 100% precision, contestable only on lexicographic criteria. Stoplist length is minimised by special treatment of monosyllables and reformulation of rules. 96% of words and phrases are analysed. 218,802 directed derivational links have been encoded in the lexicon rather than the wordnet component of the model because the lexicon provides the optimal clustering of word senses. Both links and analyser are portable to an alternative lexicon. The evaluation uses the extended gloss overlaps disambiguation algorithm. The enriched model outperformed WordNet in terms of recall without loss of precision. Failure of all experiments to outperform disambiguation by frequency reflects on WordNet sense distinctions.