People with a diagnosis of schizophrenia have been found to perform poorly on tasks assessing semantic memory, and these impairments have been proposed to be related to certain symptoms, in particular Formal Thought Disorder (FTD). A systematic literature review and meta-analysis identified the need a) to determine whether semantic memory is a primary impairment in schizophrenia and not secondary to other cognitive impairments and b) what cognitive models could provide the best explanation for the impairment. With these aims, Studies One and Two compared the performance of a group of people with schizophrenia across a battery of semantic memory tests (Hodges, Salmon and Butters, 1992). In order to eliminate confounding variables, two clinical control groups were recruited for comparison, one with a probable degraded semantic memory arising from Alzheimer‘s Dementia (AD) and the other with a primary dysexecutive syndrome caused by acquired brain injury (ABI). From these comparisons, it was possible to profile the semantic memory impairment in schizophrenia with the conclusion that any deficits are task-specific. Unlike the AD group, the impairment did not seem to arise from a loss of stored knowledge but nor did a retrieval problem, in its simplest terms, offer the best explanation. Since the ABI group performed normally on the battery it is clear that a dysexecutive syndrome does not necessarily explain poor semantic memory performance. Qualitatively, the associations and categories formed by people with schizophrenia on tasks of semantic categorisation e.g. the Category Generation Test (CGT) (Green, Done, Anthony, McKenna and Ochocki, 2004) often resemble loosening of associations and psychotic speech. In order to understand more about the processes involved in the formation of these bizarre categories, I compared performance on the CGT of groups of people with schizophrenia, AD and ABI. I found that the people with AD performed fairly similarly to the people with schizophrenia in that they sorted cards in an idiosyncratic way but the ABI group performed normally, adhering to taxonomic categories. Although this result might suggest that the bizarre associations on the CGT in people with schizophrenia are caused by a deficit in semantic memory (and not a dysexecutive syndrome), further analysis found important differences between the AD and the schizophrenia group in the way the card sorts were formed. In addition, both these groups showed intact semantic memory knowledge of the items they mis-sorted, indicating that categorisation problems do not necessarily arise from a degraded memory store. The difficulties people with schizophrenia appear to have on tests of associations and categorisation (e.g. CGT) could arise from a disorganised semantic memory i.e. differences in the way in which concepts are interconnected. On the CGT, patients with schizophrenia were far more likely to sort items on the basis of thematic (situational) information suggesting a preference for thematic over taxonomic associations. To test this, participants were tested using a triadic comparison task which requires choosing whether an item is best associated with a taxonomic, thematic or perceptually related item. On this test patients performed comparably to controls suggesting that their semantic memory is organised normally and that the abnormalities in the way in which items are associated on some semantic memory tests, including the CGT, are task-specific. It has been proposed that one of the core problems in schizophrenia is that there is ―an aberrant assignment of salience‖ (Kapur 2003) to contextually inappropriate concepts due to a dysregulated dopamine system (Kapur 2003; Kapur et al 2005). It is possible that this could also explain the semantic memory impairments in schizophrenia i.e. certain less relevant concepts/ associations are chosen because they are experienced as more salient. To test this, a group of patients with schizophrenia were assessed using a test of semantic salience. Compared to controls, the patients made significantly more errors of salience including significantly more errors where large aberrant attributions of importance were given to items. The tendency to make errors on the salience test was highly correlated with errors on the CGT and also the semantic association tests, indicating a common underlying mechanism. Therefore, it can be concluded that the semantic memory impairments in schizophrenia are task-specific, not caused by a loss of semantic knowledge or a dysexecutive syndrome, but due to an aberrant assignment of salience to less relevant semantic concepts. More work is needed to understand the cognitive processes underlying this aberrant attribution process, and also the biological substrates involved.

Cette thèse s’intéresse à l’exploitation de la sémantique de données pour la recherche exploratoire. La recherche exploratoire se réfère à des tâches de recherche qui sont très ouvertes, avec de multiples facettes, et itératives. Les données sémantiques et les données liées en particulier, offrent de nouvelles possibilités pour répondre à des requêtes de recherche et des besoins d’information complexes. Dans ce contexte, le nuage de données ouvertes liées (LOD) joue un rôle important en permettant des traitements de données avancés et des interactions innovantes. Nous détaillons un état de l’art de la recherche exploratoire sur les données liées. Puis nous proposons un algorithme de recherche exploratoire à base de données liées basé sur une recherche associative. A partir d’un algorithme de propagation d’activation nous proposons une nouvelle formule de diffusion optimisée pour les graphes typés. Nous proposons ensuite des formalisations supplémentaires de plusieurs modes d’interrogation avancée. Nous présentons également une architecture logicielle innovante basée sur deux choix de conception paradigmatiques. D’abord, les résultats doivent être calculés à la demande. Deuxièmement, les données sont consommées à distance à partir de services SPARQL distribués. Cela nous permet d’atteindre un niveau élevé de flexibilité en termes d’interrogation et de sélection des données. L’application Discovery Hub implémente ces résultats et les présente dans une interface optimisée pour l’exploration. Nous évaluons notre approche grâce à plusieurs campagnes avec des utilisateurs et nous ouvrons le débat sur de nouvelles façons d’évaluer les moteurs de recherche exploratoires. / The general topic of the thesis is web search. It focused on how to leverage the data semantics for exploratory search. Exploratory search refers to cognitive consuming search tasks that are open-ended, multi-faceted, and iterative like learning or topic investigation. Semantic data and linked data in particular offer new possibilities to solve complex search queries and information needs including exploratory search ones. In this context the linked open data cloud plays an important role by allowing advanced data processing and innovative interactions model elaboration. First, we detail a state-of-the-art review of linked data based exploratory search approaches and systems. Then we propose a linked data based exploratory search solution which is mainly based on an associative retrieval algorithm. We started from a spreading activation algorithm and proposed new diffusion formula optimized for typed graph. Starting from this formalization we proposed additional formalizations of several advanced querying modes in order to solve complex exploratory search needs. We also propose an innovative software architecture based on two paradigmatic design choices. First the results have to be computed at query-time. Second the data are consumed remotely from distant SPARQL endpoints. This allows us to reach a high level of flexibility in terms of querying and data selection. We specified, designed and evaluated the Discovery Hub web application that retrieves the results and present them in an interface optimized for exploration. We evaluate our approach thanks to several human evaluations and we open the discussion about new ways to evaluate exploratory search engines.

Submitted by Daniel Chada (danielc2112@gmail.com) on 2017-01-10T13:25:02Z No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5) / Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2017-01-12T14:03:51Z (GMT) No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5) / Made available in DSpace on 2017-01-23T11:48:10Z (GMT). No. of bitstreams: 1 chada.phd.2017.01.09.pdf: 5177057 bytes, checksum: a6174d9f2ba0b373776e750def2a23aa (MD5) Previous issue date: 2016-12-08 / Este trabalho consiste em três contribuições independentes do âmbito da modelagem cognitiva ao campo de management science. O primeiro aborda Experience Recognition, uma teoria inicialmente introduzida por Linhares e Freitas [91]. Aqui ela é estendida e delineada, além de se discutir suas contribuições para a ciência cognitiva e management science. A segunda contribuição introduz a framework cognitiva chamada Rotational Sparse Distributed Memory, e fornece uma aplicação-exemplo de suas características como substrato para um fortemente relevante campo da management science: redes semânticas. A contribuição final aplica Rotational Sparse Distributed Memory para a modelagem de motifs de rede, flexibilidade dinâmica e organização hierárquica, três resultados de forte impacto na literatura recente de neurociência. A relevância de uma abordagem baseada na modelagem neurocientífica para a decision science é discutida. / This work is comprised of three independent contributions from the realm of cognitive modeling to management science. The first addresses Experience Recognition, a theory first introduced by Linhares and Freitas [91]. Here it is extended and better defined, and also its contribution to cognitive science and management science are discussed. The second contribution introduces a cognitive framework called Rotational Sparse Distributed Memory, and provides a sample application of its characteristics as a substrate for a highly relevant subject in management science: semantic networks. The final contribution applies Rotational Sparse Distributed Memory to modeling network motifs, dynamic flexibility and hierarchical organization, all highly impactful results in recent neuroscience literature. The relevance of a neuroscientific modeling approach towards a cognitive view of decision science are discussed.

This dissertation investigates how cognates are organized in the bilingual mental lexicon and examines whether orthography in one language, via phonological representations, influences the processing of cognates and false friends in the other language. In light of the framework of two well-known models of bilingual visual word recognition, the Bilingual Interactive Activation (BIA) and the Bilingual Interactive Activation Plus (BIA+), the premise is that there is activation from orthography to phonology across a bilingual’s two languages and that this activation is modulated by the degree of orthographic and phonological code overlap. Two objective metrics were used to assess crosslinguistic similarity of Portuguese-English cognates and false friends that were selected for a cross-language lexical decision task with masked priming. Dynamic time warping (DTW), an algorithm that was originally conceived to compare different speech patterns in automatic speech recognition and to measure acoustic similarity between two time-dependent sequences, was used to compute crosslinguistic phonological similarity. The Normalized Levenshtein Distance (NLD), an algorithm that calculates the minimum number of single-character insertions, deletions or substitutions required to change one word into another and normalizes the result by their lengths, was used to compute crosslinguistic orthographic similarity. Portuguese-English bilinguals who acquired their second language after reaching puberty, and English functional monolinguals who grew up speaking primarily English were recruited to participate in the experimental task. Based on collected reaction time and accuracy data, mixed-effects models analyses are used to estimate the individual effects of crosslinguistic orthographic, phonological and semantic similarity and the role each of them, along with English proficiency, word frequency and length play in the organization of the Portuguese-English bilingual mental lexicon.