La transferencia en la clínica con niños : Continuidades y rupturas

Cada marco teórico recorta una dimensión posible respecto del funcionamiento del aparato psíquico, dando lugar a la puesta en forma de los alcances y los límites, a partir de los cuales se delimitan vías posibles de intervención. En el entramado que allí se constituye, el concepto de transferencia encuentra su asiento. Ahora bien, ¿qué rasgos de particularidad atraviesan las nociones conceptuales cuando se emplazan y articulan con los movimientos fundacionales que dan cuenta de los tiempos de constitución psíquica? Determinar la singularidad de los conceptos, desde su emplazamiento en la red conceptual que cerca los tiempos de la constitución, supone remitirse a los inicios de una práctica. Para ello, se circunscribirán ciertas coordenadas que darán cuenta del trayecto teórico-clínico propuesto por aquellos autores que trazaron el origen de la clínica con niños y adolescentes. La presente investigación se conforma a partir de las propuestas de trabajo dadas en el marco de la carrera de Especialización en Clínica Psicoanalítica con Niños y Adolescentes de la Facultad de Psicología de la UNLP, cuya directora es la profesora psicóloga Norma Najt

La transferencia en la clínica con niños : Continuidades y rupturas

Cada marco teórico recorta una dimensión posible respecto del funcionamiento del aparato psíquico, dando lugar a la puesta en forma de los alcances y los límites, a partir de los cuales se delimitan vías posibles de intervención. En el entramado que allí se constituye, el concepto de transferencia encuentra su asiento. Ahora bien, ¿qué rasgos de particularidad atraviesan las nociones conceptuales cuando se emplazan y articulan con los movimientos fundacionales que dan cuenta de los tiempos de constitución psíquica? Determinar la singularidad de los conceptos, desde su emplazamiento en la red conceptual que cerca los tiempos de la constitución, supone remitirse a los inicios de una práctica. Para ello, se circunscribirán ciertas coordenadas que darán cuenta del trayecto teórico-clínico propuesto por aquellos autores que trazaron el origen de la clínica con niños y adolescentes. La presente investigación se conforma a partir de las propuestas de trabajo dadas en el marco de la carrera de Especialización en Clínica Psicoanalítica con Niños y Adolescentes de la Facultad de Psicología de la UNLP, cuya directora es la profesora psicóloga Norma Najt

MIRACLE at Ad-Hoc CLEF 2005: Merging and Combining Without Using a Single Approach

This paper presents the 2005 Miracle’s team approach to the Ad-Hoc Information Retrieval tasks. The goal for the experiments this year was twofold: to continue testing the effect of combination approaches on information retrieval tasks, and improving our basic processing and indexing tools, adapting them to new languages with strange encoding schemes. The starting point was a set of basic components: stemming, transforming, filtering, proper nouns extraction, paragraph extraction, and pseudo-relevance feedback. Some of these basic components were used in different combinations and order of application for document indexing and for query processing. Second-order combinations were also tested, by averaging or selective combination of the documents retrieved by different approaches for a particular query. In the multilingual track, we concentrated our work on the merging process of the results of monolingual runs to get the overall multilingual result, relying on available translations. In both cross-lingual tracks, we have used available translation resources, and in some cases we have used a combination approach.

Characterising emergent semantics in Twitter lists

Twitter lists organise Twitter users into multiple, often overlapping, sets. We believe that these lists capture some form of emergent semantics, which may be useful to characterise. In this paper we describe an approach for such characterisation, which consists of deriving semantic relations between lists and users by analyzing the cooccurrence of keywords in list names. We use the vector space model and Latent Dirichlet Allocation to obtain similar keywords according to co-occurrence patterns. These results are then compared to similarity measures relying on WordNet and to existing Linked Data sets. Results show that co-occurrence of keywords based on members of the lists produce more synonyms and more correlated results to that of WordNet similarity measures.

Descubrimiento de mappings en recursos geoespaciales

La integración de fuentes de información heterogéneas ha sido un problema abordado en diferentes tipos de fuentes a lo largo de las décadas de diferentes maneras. Una de ellas es el establecimiento de unas relaciones semánticas que permitan poder unir la información de las fuentes relacionadas. A estos enlaces, claves en la integración, se les ha llamado generalmente mappings. Los mappings se han usado en multitud de trabajos y se han abordado, de manera más práctica que teórica en muchos casos, diferentes soluciones para su descubrimiento, su almacenaje, su explotación, etc. Sin embargo, aunque han sido muchas las contribuciones sobre mappings, no hay una definición generalizada y admitida por la comunidad que cubra todos los aspectos vinculados a los mappings. Además, en su proceso de descubrimiento, no existe un marco teórico que defina metódicamente los procesos a seguir y sus características. Igualmente, la actual forma de evaluar el descubrimiento de mappings no es suficiente para toda la casuística existente. En este trabajo se aporta una definición de mapping génerica que engloba todos los sistemas actuales, la especificación detallada del proceso de descubrimiento y el análisis y la propuesta de un proceso de evaluación del descubrimiento. La validez de estos aportes se comprueba con la formulación de hipótesis y su comprobación mediante un estudio cuantitativo sobre un caso de uso con recursos geoespaciales heterogéneos. ABSTRACT The integration of heterogeneous information resources has been an issue addressed in different types of sources over the decades in different ways. One of them is the establishment of semantic relations which allow information from different related resources to be linked. These links, crucial pieces of this integration, are usually known as mappings. These mappings have been widely used in many applications, and different solutions for their discovery, storing, explotation, etc. have been presented, following rather a more practical than theoretical way in many cases. However, although mappings have been widely applied by many researchers, there is a lack of a generally accepted definition that can cover all the aspects related to mappings. Moreover, in the process of mapping discovery, there is not a theoretical framework that defines methodically the processes to be followed and their characteristics. Similarly, the current way of assessing or evaluating the discovery of mappings is insufficient for all the existing use cases. The main contributions of this work are threefold. On the one hand, it presents a general definition of "mapping" which covers all current systems. On the other hand, it describes a detailed specification of the discovery process, and, finally, it faces the analysis and the purpose of the evaluation of this discovery process. The validity of these contributions has been checked with the formulation of hypothesis which have been verified by using heterogeneous geospatial resources in a quantitative study.

An approach based on Logic Forms and WordNet relationships to Textual Entailment performance

This paper outlines the approach adopted by the PLSI research group at University of Alicante in the PASCAL-2006 second Recognising Textual Entailment challenge. Our system is composed of several components. On the one hand, the first component performs the derivation of the logic forms of the text/hypothesis pairs and, on the other hand, the second component provides us with a similarity score given by the semantic relations between the derived logic forms. In order to obtain this score we apply several measures of similitude and relatedness based on the structure and content of WordNet.

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.

Integration and querying of heterogeneous, autonomous, distributed database systems

Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. ^ This thesis describes a heterogeneous database system being developed at High-performance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii) a framework for intelligent computing and communication on the Internet applying the concepts of our work. ^

Integration and querying of heterogeneous, autonomous, distributed database systems

Today, databases have become an integral part of information systems. In the past two decades, we have seen different database systems being developed independently and used in different applications domains. Today's interconnected networks and advanced applications, such as data warehousing, data mining & knowledge discovery and intelligent data access to information on the Web, have created a need for integrated access to such heterogeneous, autonomous, distributed database systems. Heterogeneous/multidatabase research has focused on this issue resulting in many different approaches. However, a single, generally accepted methodology in academia or industry has not emerged providing ubiquitous intelligent data access from heterogeneous, autonomous, distributed information sources. This thesis describes a heterogeneous database system being developed at Highperformance Database Research Center (HPDRC). A major impediment to ubiquitous deployment of multidatabase technology is the difficulty in resolving semantic heterogeneity. That is, identifying related information sources for integration and querying purposes. Our approach considers the semantics of the meta-data constructs in resolving this issue. The major contributions of the thesis work include: (i.) providing a scalable, easy-to-implement architecture for developing a heterogeneous multidatabase system, utilizing Semantic Binary Object-oriented Data Model (Sem-ODM) and Semantic SQL query language to capture the semantics of the data sources being integrated and to provide an easy-to-use query facility; (ii.) a methodology for semantic heterogeneity resolution by investigating into the extents of the meta-data constructs of component schemas. This methodology is shown to be correct, complete and unambiguous; (iii.) a semi-automated technique for identifying semantic relations, which is the basis of semantic knowledge for integration and querying, using shared ontologies for context-mediation; (iv.) resolutions for schematic conflicts and a language for defining global views from a set of component Sem-ODM schemas; (v.) design of a knowledge base for storing and manipulating meta-data and knowledge acquired during the integration process. This knowledge base acts as the interface between integration and query processing modules; (vi.) techniques for Semantic SQL query processing and optimization based on semantic knowledge in a heterogeneous database environment; and (vii.) a framework for intelligent computing and communication on the Internet applying the concepts of our work.

LOGO: GRAMMATICALIZATION AND SEMANTICS IN MEDIA TEXTS

It is a fact that the study and the correct application of the rules of Portuguese grammar are necessary for the issuer to communicate adequately in most discursive genres. However this same grammar imposes certain rules that now left to be used due to historical developments that pervade any language, now began to be employed so not always equal to those advocated by the normative grammar. Wherefore to understand situations which are not justified by traditional grammar, theories that are sought to assist this understanding. The current adopted will be the Functionalism, which promotes linguistic analysis beyond established by normative grammar, it covers other aspects not considered by her. Looking enlarger the discussions about the different uses, this study is aimed at ascertaining what is mentioned by the normative and functionalists studies with respect to the word logo, traditionally defined as a coordinating conjunction conclusive. Furthermore, we seek to show the process of grammaticalization whereby the term came and expose the different semantic relations that he can express in language use. To prove this, was used everyday examples, took out from media texts, such as magazine Isto É and the newspaper Folha de S. Paulo.

Differential processing of thematic and categorical conceptual relations in spoken word production

Studies of semantic context effects in spoken word production have typically distinguished between categorical (or taxonomic) and associative relations. However, associates tend to confound semantic features or morphological representations, such as whole-part relations and compounds (e.g., BOAT-anchor, BEE-hive). Using a picture-word interference paradigm and functional magnetic resonance imaging (fMRI), we manipulated categorical (COW-rat) and thematic (COW-pasture) TARGET-distractor relations in a balanced design, finding interference and facilitation effects on naming latencies, respectively, as well as differential patterns of brain activation compared with an unrelated distractor condition. While both types of distractor relation activated the middle portion of the left middle temporal gyrus (MTG) consistent with retrieval of conceptual or lexical representations, categorical relations involved additional activation of posterior left MTG, consistent with retrieval of a lexical cohort. Thematic relations involved additional activation of the left angular gyrus. These results converge with recent lesion evidence implicating the left inferior parietal lobe in processing thematic relations and may indicate a potential role for this region during spoken word production.

Cross-participant modelling based on joint or disjoint feature selection: an fMRI conceptual decoding study

Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

Translation and cultural adaptation of Brazilian Detailed Assessment of Speed of Handwriting: conceptual and semantic equivalence

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

The impact of Internet marketing capabilities on international network capability, a cross country study comparison between Australia, Chile and Taiwan internationalised SMEs

The Internet has been shown to positively enhance internationalisation for SMEs, but scant empirical testing limits our understanding of the explicit impact of the Internet on firm internationalisation. This paper highlights key areas where the integration of the Internet can be leveraged through Internet-related capabilities within the internationalisation of the firm. Specifically, this study investigates how Internet marketing capabilities play a role in altering international information availability, international strategic orientation, and international business network relationships. This study provides evidence, indicating that these key relationships may vary between countries. To examine these key relationships this study utilises draws from data small and medium sized enterprises (SMEs) in three export intensive markets; Australia (215 international SMEs), Chile (204 international SMEs) and Taiwan (130 international SMEs); and tests a conceptual model through structural equation modelling. Results from the data show the impact of Internet marketing capabilities in positively impacting traditional internationalisation elements, which varies between countries. That is, our findings highlight the international business network relationships in Australia and Taiwan are directly impacted by Internet marketing capabilities, but not in Chile. We offer some insight into why we see variance across comparative exporting countries in how they leverage new technological capabilities for internationalisation and firm performance.