User's guide to EUREKA and EURUP /

Bibliography: p. 95.

Notes on AVL trees /

"Written as supplementary material for a course in data structures given by the Dept. of Computer Science of the University of Illinois at Urbana-Champaign, during the second semester of the 1970-71 academic year"--Leaf 1.

EDGAR : a status report /

"June 30, 1987."

Thesaurus for SOYA : computerized bibliographic database on soybean utilization, processing, marketing nutrition, production, and history, 1100 B.C. to the 1980s /

Mode of access: Internet.

Resources in education /

"Made up of resumés and indexes of documents [of educational significance] ... numbered sequentially with ED prefixes and current Office of Education research projects [with EP prefixes]".

Interface de recuperación para catálogos en línea con salidas ordenadas por probable relevancia

Se presenta el desarrollo de una interface de recuperación de información para catálogos en línea de acceso público (plataforma CDS/ISIS), basada en el concepto de similaridad para generar los resultados de una búsqueda ordenados por posible relevancia. Se expresan los fundamentos teóricos involucrados, para luego detallar la forma en que se efectuó su aplicación tecnológica, explícita a nivel de programación. Para finalizar se esbozan los problemas de implementación según el entorno

Planetary Penetrators for Sample Return Missions

Thesis (Master's)--University of Washington, 2016-06

Fitness assessment of document model

Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

How does your model grow? An empirical investigation of the effects of ontological clarity and application domain size on query performance

Semantic data models provide a map of the components of an information system. The characteristics of these models affect their usefulness for various tasks (e.g., information retrieval). The quality of information retrieval has obvious important consequences, both economic and otherwise. Traditionally, data base designers have produced parsimonious logical data models. In spite of their increased size, ontologically clearer conceptual models have been shown to facilitate better performance for both problem solving and information retrieval tasks in experimental settings. The experiments producing evidence of enhanced performance for ontologically clearer models have, however, used application domains of modest size. Data models in organizational settings are likely to be substantially larger than those used in these experiments. This research used an experiment to investigate whether the benefits of improved information retrieval performance associated with ontologically clearer models are robust as the size of the application domains increase. The experiment used an application domain of approximately twice the size as tested in prior experiments. The results indicate that, relative to the users of the parsimonious implementation, end users of the ontologically clearer implementation made significantly more semantic errors, took significantly more time to compose their queries, and were significantly less confident in the accuracy of their queries.

Dissecting query performance in logical data models: Parsimony vs. greater ontological clarity

Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.

O LÚDICO VIA FÁBULAS EM ATENDIMENTO PSICOTERAPÊUTICO: UM ESTUDO DE CASO CLÍNICO DE MOBBING

Esta pesquisa verifica a validade da utilização de fábulas em processo psicoterapêutico de paciente de Mobbing acometida de depressão e síndrome de pânico. Desenvolve-se por meio de estudo de caso avaliativo-interventivo evolutivo prolongado, com um total de 116 sessões semanais. Inicialmente realiza o diagnóstico clínico elaborado a partir do desenho da figura humana, extraído do teste projetivo House Tree and Person, de entrevista inicial semi-dirigida, e de coleta de relatos verbais e observações feitas durante os primeiros atendimentos. As sessões são realizadas com utilização ocasional de fábulas, associada ou não a técnicas de relaxamento de Schultz e Jacobson, com interpretação de sonhos e recomendação de filmes. O objetivo é verificar se as fábulas contribuem de forma positiva para o paciente compreender com mais facilidade as interpretações do psicoterapeuta, se diminui sua resistência ao falar dos seus conteúdos e se amplia à consciência simbólica. O primeiro momento interventivo tem a duração de aproximadamente 16 meses, o segundo, de 04 meses, quando é solicitado o segundo desenho e o terceiro processa-se em 09 meses, quando é solicitado o último desenho. No primeiro momento é proporcionado à paciente um ambiente facilitador com sustentação emocional (Holding), buscando resgatar sua ilusão, numa visão winnicottiana. Revela-se uma situação de Mobbing acompanhada de depressão manifesta e síndrome do pânico; com alto nível de exigência pessoal e profissional; grande passividade nos relacionamentos e na dinâmica do casal. Ao final desse momento, já consegue começar a desviar sua auto-agressividade para o meio externo de maneira mais positiva e socialmente aceita. No segundo momento predomina o encontro e aceitação de seu verdadeiro jeito de ser; enxerga o quanto estava se deixando prejudicar; mostra-se mais confiante, comunica-se e enfrenta melhor suas dificuldades afetivas. No terceiro momento demonstra estar segura e feliz. Cuida de sua aparência e sente prazer em ser notada socialmente. Demonstra ter aprendido a se defender em situações de confronto, com maior autonomia e verbaliza estar muito feliz com as mudanças, sorri com freqüência. A análise evolutiva dos desenhos confirmam esta boa evolução. A utilização de fábulas foi muito bem aceita pela paciente, que conseguiu por meio da leitura simbólica contida nas mesmas, aproximar-se de sua problemática e aprender a lidar com ela de forma mais saudável. Os resultados também indicam que a utilização de relaxamento associado à leitura das fábulas contribuiu para sua assimilação mais abrangente e profunda. O estudo ilustra a evolução do caso por meio de 24 vinhetas, devidamente analisadas em relação aos momentos descritos.(AU)

A comparative evaluation of term recognition algorithms

Automatic Term Recognition (ATR) is a fundamental processing step preceding more complex tasks such as semantic search and ontology learning. From a large number of methodologies available in the literature only a few are able to handle both single and multi-word terms. In this paper we present a comparison of five such algorithms and propose a combined approach using a voting mechanism. We evaluated the six approaches using two different corpora and show how the voting algorithm performs best on one corpus (a collection of texts from Wikipedia) and less well using the Genia corpus (a standard life science corpus). This indicates that choice and design of corpus has a major impact on the evaluation of term recognition algorithms. Our experiments also showed that single-word terms can be equally important and occupy a fairly large proportion in certain domains. As a result, algorithms that ignore single-word terms may cause problems to tasks built on top of ATR. Effective ATR systems also need to take into account both the unstructured text and the structured aspects and this means information extraction techniques need to be integrated into the term recognition process.