986 resultados para Question-Answering System
Resumo:
This research explores the advantages and disadvantages of collaborative learning departing from two different methodological studies. In the first one, we will go deep into the reflections about group work of a student-teacher in her first experiences during a two months practicum in Sabadell's Emily Bronte. In the second one, we will analyze in a more empirical way the interaction that takes place among a trio of students engaged in a question-answering task about a text based on a three minutes vignette recorded on January 2010
Resumo:
El projecte Disseny i Implementació d'una xarxa d'experts, té com a objectiu principal la construcció d'una eina per a la gestió del coneixement d'un entorn acotat a través d'un sistema de pregunta-resposta basat en experts en diferents temàtiques. L'establiment d'aquest sistema ha de permetre a l'usuari obtenir la informació que necessita dotant-li d'eines per accedir a les fonts de coneixement, en el nostre cas les persones identificades com a experts, amb una enorme facilitat. A més a més, durant tot el projecte s'ha tingut molt en compte les alternatives opensource que existeixen al mercat i la possibilitat d'adaptació que poden donar davant d'altres alternatives.
Resumo:
Resumen de la sesión organizada por Socadi (Sociedad Catalana de Documentación e Información) a finales de enero pasado en Barcelona sobre intranets, o sea, sobre los sistemas que aplican la tecnología web para gestionar información, documentación y comunicación en una organización.
Resumo:
Everyday tasks seldom involve isolate actions but sequences of them. We can see whether previous actions influence the current one by exploring the response time to controlled sequences of stimuli. Specifically, depending on the response-stimulus temporal interval (RSI), different mechanisms have been proposed to explain sequential effects in two-choice serial response tasks. Whereas an automatic facilitation mechanism is thought to produce a benefit for response repetitions at short RSIs, subjective expectancies are considered to replace the automatic facilitation at longer RSIs, producing a cost-benefit pattern: repetitions are faster after other repetitions but they are slower after alternations. However, there is not direct evidence showing the impact of subjective expectancies on sequential effects. By using a fixed sequence, the results of the reported experiment showed that the repetition effect was enhanced in participants who acquired complete knowledge of the order. Nevertheless, a similar cost-benefit pattern was observed in all participants and in all learning blocks. Therefore, results of the experiment suggest that sequential effects, including the cost-benefit pattern, are the consequence of automatic mechanisms which operate independently of (and simultaneously with) explicit knowledge of the sequence or other subjective expectancies.
Resumo:
This experimental study examined the effects of cooperative learning and a question-answering strategy called elaborative interrogation ("Why is this fact true?") on the learning of factual information about familiar animals. Retention gains were compared across four study conditions: elaborative-interrogation-plus-cooperative learning, cooperative-learning, elaborative-interrogation, and reading-control. Sixth-grade students (n=68) were randomly assigned to the four conditions. All participants were given initial training and practice in cooperative learning procedures via three 45-minute sessions. After studying 36 facts about six animals, students' retention gains were measured via immediate free recall, immediate matched association, 30-day, and GO-day matched association tests. A priori comparisons were made to analyze the data. For immediate free recall and immediate matched association, significant differences were found between students in the three experimental conditions versus those in the control condition. Elaborative-interrogation and elaborativeinterrogation- plus-cooperative-learning also promoted longterm retention (measured via 30-day matched association) of the material relative to repetitive reading with elaborative-interrogation promoting the most durable gains (measured via GO-day matched association). The relationship between the types of elaborative responses and probability of subsequent retention was also examined. Even when students were unable to provide adequate answers to the why questions, learning was facilitated more so than repetitive reading. In general, generation of adequate elaborations was associated with greater probability of recall than was provision of inadequate answers. The findings of the study demonstrate that cooperative learning and the use of elaborative interrogation, both individually and collaboratively, are effective classroom procedures for facilitating children's learning of new information.
Resumo:
This study examined the efficacy of providing four Grade 7 and 8 students with reading difficulties with explicit instruction in the use of reading comprehension strategies while using text-reader software. Specifically, the study explored participants' combined use of a text-reader and question-answering comprehension strategy during a 6-week instructional program. Using a qualitative case study methodology approach, participants' experiences using text-reader software, with the presence of explicit instruction in evidence-based reading comprehension strategies, were examined. The study involved three phases: (a) the first phase consisted of individual interviews with the participants and their parents; (b) the second phase consisted of a nine session course; and (c) the third phase consisted of individual exit interviews and a focus group discussion. After the data collection phases were completed, data were analyzed and coded for emerging themes, with-quantitativ,e measures of participants' reading performance used as descriptive data. The data suggested that assistive technology can serve as an instructional "hook", motivating students to engage actively in the reading processes, especially when accompanied by explicit strategy instruction. Participants' experiences also reflected development of strategy use and use of text-reader software and the importance of social interactions in developing reading comprehension skills. The findings of this study support the view that the integration of instruction using evidence-based practices are important and vital components in the inclusion oftext-reader software as part of students' educational programming. Also, the findings from this study can be extended to develop in-class programming for students using text-reader software.
Resumo:
Quand le E-learning a émergé il ya 20 ans, cela consistait simplement en un texte affiché sur un écran d'ordinateur, comme un livre. Avec les changements et les progrès dans la technologie, le E-learning a parcouru un long chemin, maintenant offrant un matériel éducatif personnalisé, interactif et riche en contenu. Aujourd'hui, le E-learning se transforme de nouveau. En effet, avec la prolifération des systèmes d'apprentissage électronique et des outils d'édition de contenu éducatif, ainsi que les normes établies, c’est devenu plus facile de partager et de réutiliser le contenu d'apprentissage. En outre, avec le passage à des méthodes d'enseignement centrées sur l'apprenant, en plus de l'effet des techniques et technologies Web2.0, les apprenants ne sont plus seulement les récipiendaires du contenu d'apprentissage, mais peuvent jouer un rôle plus actif dans l'enrichissement de ce contenu. Par ailleurs, avec la quantité d'informations que les systèmes E-learning peuvent accumuler sur les apprenants, et l'impact que cela peut avoir sur leur vie privée, des préoccupations sont soulevées afin de protéger la vie privée des apprenants. Au meilleur de nos connaissances, il n'existe pas de solutions existantes qui prennent en charge les différents problèmes soulevés par ces changements. Dans ce travail, nous abordons ces questions en présentant Cadmus, SHAREK, et le E-learning préservant la vie privée. Plus précisément, Cadmus est une plateforme web, conforme au standard IMS QTI, offrant un cadre et des outils adéquats pour permettre à des tuteurs de créer et partager des questions de tests et des examens. Plus précisément, Cadmus fournit des modules telles que EQRS (Exam Question Recommender System) pour aider les tuteurs à localiser des questions appropriées pour leur examens, ICE (Identification of Conflits in Exams) pour aider à résoudre les conflits entre les questions contenu dans un même examen, et le Topic Tree, conçu pour aider les tuteurs à mieux organiser leurs questions d'examen et à assurer facilement la couverture des différent sujets contenus dans les examens. D'autre part, SHAREK (Sharing REsources and Knowledge) fournit un cadre pour pouvoir profiter du meilleur des deux mondes : la solidité des systèmes E-learning et la flexibilité de PLE (Personal Learning Environment) tout en permettant aux apprenants d'enrichir le contenu d'apprentissage, et les aider à localiser nouvelles ressources d'apprentissage. Plus précisément, SHAREK combine un système recommandation multicritères, ainsi que des techniques et des technologies Web2.0, tels que le RSS et le web social, pour promouvoir de nouvelles ressources d'apprentissage et aider les apprenants à localiser du contenu adapté. Finalement, afin de répondre aux divers besoins de la vie privée dans le E-learning, nous proposons un cadre avec quatre niveaux de vie privée, ainsi que quatre niveaux de traçabilité. De plus, nous présentons ACES (Anonymous Credentials for E-learning Systems), un ensemble de protocoles, basés sur des techniques cryptographiques bien établies, afin d'aider les apprenants à atteindre leur niveau de vie privée désiré.
Resumo:
O presente trabalho tem por objetivo subsidiar o investidor de Fundos de Investimento Imobiliário na escolha de uma carteira de aplicação de FIIs, visando obter performance igual ou superior ao índice de referência do setor (IFIX). Tal subsídio é constituído, inicialmente, por uma metodologia que considera que o conceito de Carteira Eficiente (Risco/Retorno) preconizada por Markowitz pode trabalhar em conjunto com a dimensão do conceito das Finanças Comportamentais, liderada por Daniel Kahneman, constituindo as bases de orientação do investidor. Acrescentamos o caminho metodológico com as indicações, sugeridas por Bazerman e Moore, no processo de tomada de decisão, que reduza os efeitos de heurísticas e vieses.
Resumo:
This paper introduces a semantic language developed with the objective to be used in a semantic analyzer based on linguistic and world knowledge. Linguistic knowledge is provided by a Combinatorial Dictionary and several sets of rules. Extra-linguistic information is stored in an Ontology. The meaning of the text is represented by means of a series of RDF-type triples of the form predicate (subject, object). Semantic analyzer is one of the options of the multifunctional ETAP-3 linguistic processor. The analyzer can be used for Information Extraction and Question Answering. We describe semantic representation of expressions that provide an assessment of the number of objects involved and/or give a quantitative evaluation of different types of attributes. We focus on the following aspects: 1) parametric and non-parametric attributes; 2) gradable and non-gradable attributes; 3) ontological representation of different classes of attributes; 4) absolute and relative quantitative assessment; 5) punctual and interval quantitative assessment; 6) intervals with precise and fuzzy boundaries
Resumo:
This paper presents a preliminary study in which Machine Learning experiments applied to Opinion Mining in blogs have been carried out. We created and annotated a blog corpus in Spanish using EmotiBlog. We evaluated the utility of the features labelled firstly carrying out experiments with combinations of them and secondly using the feature selection techniques, we also deal with several problems, such as the noisy character of the input texts, the small size of the training set, the granularity of the annotation scheme and the language object of our study, Spanish, with less resource than English. We obtained promising results considering that it is a preliminary study.
Resumo:
The goal of the project is to analyze, experiment, and develop intelligent, interactive and multilingual Text Mining technologies, as a key element of the next generation of search engines, systems with the capacity to find "the need behind the query". This new generation will provide specialized services and interfaces according to the search domain and type of information needed. Moreover, it will integrate textual search (websites) and multimedia search (images, audio, video), it will be able to find and organize information, rather than generating ranked lists of websites.
Resumo:
El campo de procesamiento de lenguaje natural (PLN), ha tenido un gran crecimiento en los últimos años; sus áreas de investigación incluyen: recuperación y extracción de información, minería de datos, traducción automática, sistemas de búsquedas de respuestas, generación de resúmenes automáticos, análisis de sentimientos, entre otras. En este artículo se presentan conceptos y algunas herramientas con el fin de contribuir al entendimiento del procesamiento de texto con técnicas de PLN, con el propósito de extraer información relevante que pueda ser usada en un gran rango de aplicaciones. Se pueden desarrollar clasificadores automáticos que permitan categorizar documentos y recomendar etiquetas; estos clasificadores deben ser independientes de la plataforma, fácilmente personalizables para poder ser integrados en diferentes proyectos y que sean capaces de aprender a partir de ejemplos. En el presente artículo se introducen estos algoritmos de clasificación, se analizan algunas herramientas de código abierto disponibles actualmente para llevar a cabo estas tareas y se comparan diversas implementaciones utilizando la métrica F en la evaluación de los clasificadores.
Resumo:
Automatic Text Summarization has been shown to be useful for Natural Language Processing tasks such as Question Answering or Text Classification and other related fields of computer science such as Information Retrieval. Since Geographical Information Retrieval can be considered as an extension of the Information Retrieval field, the generation of summaries could be integrated into these systems by acting as an intermediate stage, with the purpose of reducing the document length. In this manner, the access time for information searching will be improved, while at the same time relevant documents will be also retrieved. Therefore, in this paper we propose the generation of two types of summaries (generic and geographical) applying several compression rates in order to evaluate their effectiveness in the Geographical Information Retrieval task. The evaluation has been carried out using GeoCLEF as evaluation framework and following an Information Retrieval perspective without considering the geo-reranking phase commonly used in these systems. Although single-document summarization has not performed well in general, the slight improvements obtained for some types of the proposed summaries, particularly for those based on geographical information, made us believe that the integration of Text Summarization with Geographical Information Retrieval may be beneficial, and consequently, the experimental set-up developed in this research work serves as a basis for further investigations in this field.
Resumo:
Includes bibliographical references.
Resumo:
Online communities are prime sources of information. The Web is rich with forums and Question Answering (Q&A) communities where people go to seek answers to all kinds of questions. Most systems employ manual answer-rating procedures to encourage people to provide quality answers and to help users locate the best answers in a given thread. However, in the datasets we collected from three online communities, we found that half their threads lacked best answer markings. This stresses the need for methods to assess the quality of available answers to: 1) provide automated ratings to fill in for, or support, manually assigned ones, and; 2) to assist users when browsing such answers by filtering in potential best answers. In this paper, we collected data from three online communities and converted it to RDF based on the SIOC ontology. We then explored an approach for predicting best answers using a combination of content, user, and thread features. We show how the influence of such features on predicting best answers differs across communities. Further we demonstrate how certain features unique to some of our community systems can boost predictability of best answers.