The influence of finger-counting strategies (pointing, keep track, montring) on number representations is supported by several empirical facts. However, even the above mentioned strategies have been object of studies during childhood, little is known about how finger-counting could interact with the semantic representation of numbers in adulthood. To address this issue, we conducted a first experiment in which participants had to identify Arabic digits by pressing the keyboard with one between their ten fingers. Results showed that responses were faster and more accurate when the finger assigned to each digit was congruent with the finger-counting habits of the participants (Di Luca, Granà, Semenza, Seron and Pesenti, 2006). Subsequently, in a numerosity detection task, we showed that the numerosities expressed by canonical configurations are named faster than those expressed by non-canonical ones, even when no motors responses were needed (Di Luca and Pesenti, in press). Moreover, when used as unconsciously presented primes, both types of configurations speeded up comparative judgments of Arabic digits, but only the priming effect induced by canonical configurations generalized to new, never consciously seen, numerosities, which implies an automatic semantic access for these one only. Finally, we showed that these differences cannot be ascribed to simple visual features, but they stem from two distinct semantic processes. Specifically, canonical configurations are processed as a symbolic system and activate a place coding semantic representation of magnitude, whereas non-canonical configurations activate a summation coding semantic representation.

This degree project is mainly discussing about a web service classification approach based on suffix tree algorithm. Nowadays, Web Services are made up of WSDL web Service, RESTful web Service and many traditional component Services on Internet. The cost of manual classification cannot satisfy the increasing web services, so this paper proposes an approach to automatically classify web service because of this approach only relies on the textual description of service. Though semantic similarity calculation, we achieve web service classification automatically. Experimental evaluation results show that this approach has an acceptable and stable efficiency on precision and recall.

Content Management Systems (CMS) generally store data in a way that the content is distributed among several relational database tables or stored in files as a whole without any distinctive characteristics. These storage mechanisms cannot provide the management of semantic information about the data. They lack semantic retrieval, search and browsing of the stored content. To enhance non-semantic CMSes with advanced semantic features, the semantics within the CMS itself and additional semantic information related with the actual managed content should also be taken into account. However, extracting implicit knowledge from the legacy CMSes, lifting to a semantic content management system environment and providing semantic operations on the content is a challenging task which includes adoption of several latest advancements in information extraction (IE), information retrieval (IR) and Semantic Web areas. In this study, we propose an integrative approach including automatic lifting of content from legacy systems, automatic annotation of data with the information retrieved from the Linked Open Data (LOD) cloud and several semantic operations on the content in terms of storage and search. We use a simple RDF path language to create custom, semantic indexes and filter annotations obtained from LOD cloud in a way that is eligible for specific use cases. Filtered annotations are materialized along with the actual content of document in dedicated indexes. This semantix indexing infrastructure allows semantically meaningful search facilities on top of it. We realize our approach in the scope of Apache Stanbol project, which is a subproject developed in the scope of IKS project, by focusing on document storage and retrival parts of it. We evaluate our approach in healthcare domain with different domain ontologies (SNOMED/CT, ART, RXNORM) in addition to DBpedia as parts of LOD cloud which are used annotate documents and content obtained from different health portals.

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

An early vision in Computer Science was to create intelligent systems ca- pable of reasoning on large amounts of data. Independent results in the areas of Description Logic and Relational Databases have advanced us towards this vision. Description Logic research has advanced the understanding of the tradeoff between the computational complexity of reasoning and the expressiveness of logic languages, and now underpins the Semantic Web. The Semantic Web comprises a graph data model (RDF), an ontology language for knowledge representation and reasoning (OWL) and a graph query language (SPARQL). Database research has advanced the theory and practice of management of data, embodying features such as views and recursion which are capable of representing reasoning. Despite the independent advances, the interface between Relational Databases and Semantic Web is poorly understood. This dissertation revisits this vision with respect to current technology and addresses the following question: How and to what extent can Relational Databases be integrated with the Semantic Web? The thesis is that much of the existing Relational Database infrastructure can be reused to support the Semantic Web. Two problems are studied. Can a Relational Database be automatically virtualized as a Semantic Web data source? This paradigm comprises a single Relational Database. The first contribution is an automatic direct mapping from a Relational Database schema and data to RDF and OWL. The second contribution is a method capable of evalu- ating SPARQL queries against the Relational Database, per the direct mapping, by exploiting two existing relational query optimizations. These contributions are embodied in a system called Ultrawrap. Empirical analysis consistently yield that SPARQL query execution performance on Ultrawrap is comparable to that of SQL queries written directly for the relational representation of the data. Such results have not been previously achieved. Can a Relational Database be mapped to existing Semantic Web ontologies and act as a reasoner? This paradigm comprises an OWL ontology including inheritance and transitivity, a Relational Database and mappings between the two. A third contribution is a method for Relational Databases to support inheritance and transitivity by compiling the ontology as mappings, implementing the mappings as SQL views, using SQL recursion and optimizing by materializing a subset of views. This contribution is implemented in an extension of Ultrawrap. Empirical analysis reveals that Relational Databases are able to effectively act as reasoners. / text

Recently Burton, Bruce and Johnston (1990) have presented an interactive activation and competition model of face recognition. They have shown that this IAC model presents a parsimonious account of semantic and repetition priming effects with faces. In addition, a number of new predictions are evident from the model's structure. One such prediction is highlighted by Burton et al. themselves - that for short prime-target stimulus onset asynchronies (SOAs) a face should prime the recognition of a target name (or vice versa), 'self priming'. This thesis examined this prediction and found that it held for a design in which items were repeated across prime type conditions (same, associated, neutral and unrelated). Further, cross (face prime/name target) and within-domain (name prime/name target) designs were found to produce equivalent degrees of self and semantic priming (Experiments 1 and 2). Closer examination of the Burton et al. model suggested that the effect of domain equivalence for self priming should not hold for a design in which the stimulus items are not repeated across prime type conditions (i.e. subjects are presented with each item only once). This prediction was confirmed in Experiments 3, 4, 5 and 6.The time courses of self and semantic priming were investigated in two experiments where the interstimulus interval (ISI) between prime and target, and prime presentation times were varied. The results proved difficult to accommodate within the Burton et al. model, but it is argued that they did not provide a sufficient basis on which to reject the model. Finally, the self priming paradigm was applied to the study of distinctiveness effects. Faces judged to be distinctive in appearance were found to produce more facilitation than faces judged to be typical in appearance. Similarly, caricatured representation of faces were found to produce more facilitation than veridical or anticaricatured representations. The results of the distinctiveness studies are discussed in terms of the Valentine's (1991a; 1991b) exemplar-based coding model and Burton, Bruce and Johnston's (1990) IAC implementation. It is concluded that the results of these experiments lend support to the Burton et al. model.

No description available.

Univ., Diplomarbeit, 2003--Frankfurt (Main) / Zsfassung in dt. und engl. Sprache

Univ., Diss.--Karlsruhe, 2005. / Literaturverz. S. [255] - 266.

Stuttgart, Univ., Diplomarbeit, 2006.