7 resultados para Thai Word segmentation

em Universidad de Alicante


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In the advent of Customer Relationship Management, a more accurate profile of the consumer is needed. The objective of this paper is to show the usefulness of knowing consumer’s complete utility function through his/her marginal utilities. This approach allows one to form groups of individuals with similar preferences (as traditional segmentation methods do) and to treat them individually (which represents an advance). The empirical application is carried out, on a sample of 2,127 individuals, in the context of tourism, where the customer relationship management philosophy is gaining more and more relevance.

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This article analyzes the solutions given in Spanish translations to the morphological creativity shown in the names of Marvel comic book characters. The English versions almost invariably provide a full description of the hero (or villain) by means of a wide variety of word-formation mechanisms leading to highly expressive charactonyms. Indeed, examples shall be listed of names of comic book heroes created through compounding, derivation, including prefixation or suffixation (both classical and Anglo-Saxon but also from other origins), lexical blending, abbreviation, clipping, onomatopoeia, and borrowings from Spanish or from other languages. Early translations into Spanish seemed to be slightly less expressive than the original, even when the same word-formation mechanism was used, usually due to either problems of transparency mainly in some of the word parts or to translation constraints. In later periods, a number of factors, including the influence from other media featuring the same characters and the general trend towards globalization through English, have led translators to choose repetition as the most frequent strategy, which has almost eliminated the creative power of wordformation mechanisms in Spanish and their ability to convey the stylistic effects found in the English versions.

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Unlike traditional approaches, new communicative trends disregard the role of word-formation mechanisms. They tend to focus on syntax and/or vocabulary without analyzing the mechanisms involved in the creation of lexical items. In this paper, based on the analysis of the use of prefixes by L2 learners in oral and written productions, as provided by the SULEC, we emphasize the advantages that word-formation awareness and knowledge may have for the learners in terms of production, creativity, understanding, autonomy, and proficiency. Through the teaching of word-formation learners may more easily decipher, decode and/or encode messages, create words they have never seen before, etc.

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We present new tools for the segmentation and analysis of musical scores in the OpenMusic computer-aided composition environment. A modular object-oriented framework enables the creation of segmentations on score objects and the implementation of automatic or semi-automatic analysis processes. The analyses can be performed and displayed thanks to customizable classes and callbacks. Concrete examples are given, in particular with the implementation of a semi-automatic harmonic analysis system and a framework for rhythmic transcription.

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En este trabajo se presenta un método para la detección de subjetividad a nivel de oraciones basado en la desambiguación subjetiva del sentido de las palabras. Para ello se extiende un método de desambiguación semántica basado en agrupamiento de sentidos para determinar cuándo las palabras dentro de la oración están siendo utilizadas de forma subjetiva u objetiva. En nuestra propuesta se utilizan recursos semánticos anotados con valores de polaridad y emociones para determinar cuándo un sentido de una palabra puede ser considerado subjetivo u objetivo. Se presenta un estudio experimental sobre la detección de subjetividad en oraciones, en el cual se consideran las colecciones del corpus MPQA y Movie Review Dataset, así como los recursos semánticos SentiWordNet, Micro-WNOp y WordNet-Affect. Los resultados obtenidos muestran que nuestra propuesta contribuye de manera significativa en la detección de subjetividad.

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Abdominal Aortic Aneurism is a disease related to a weakening in the aortic wall that can cause a break in the aorta and the death. The detection of an unusual dilatation of a section of the aorta is an indicative of this disease. However, it is difficult to diagnose because it is necessary image diagnosis using computed tomography or magnetic resonance. An automatic diagnosis system would allow to analyze abdominal magnetic resonance images and to warn doctors if any anomaly is detected. We focus our research in magnetic resonance images because of the absence of ionizing radiation. Although there are proposals to identify this disease in magnetic resonance images, they need an intervention from clinicians to be precise and some of them are computationally hard. In this paper we develop a novel approach to analyze magnetic resonance abdominal images and detect the lumen and the aortic wall. The method combines different algorithms in two stages to improve the detection and the segmentation so it can be applied to similar problems with other type of images or structures. In a first stage, we use a spatial fuzzy C-means algorithm with morphological image analysis to detect and segment the lumen; and subsequently, in a second stage, we apply a graph cut algorithm to segment the aortic wall. The obtained results in the analyzed images are pretty successful obtaining an average of 79% of overlapping between the automatic segmentation provided by our method and the aortic wall identified by a medical specialist. The main impact of the proposed method is that it works in a completely automatic way with a low computational cost, which is of great significance for any expert and intelligent system.