The WebCAT Framework — Automatic Generation of Meta-Data for Web Resources

2005 ◽  
Author(s):  
B. Martins ◽  
M.J. Silva
Keyword(s):  
Automatic Generation ◽  
Meta Data ◽  
Web Resources

scholarly journals Personalized Recommendation of Learning Objects Through Bio-inspired Algorithms and Semantic Web Technologies: an Experimental Analysis

2020 ◽  
Author(s):  
Cleon Pereira Júnior ◽  
Clarivando Francisco Belizário Júnior ◽  
Rafael D. Araújo ◽  
Fabiano A. Dorça
Keyword(s):  
Semantic Web ◽  
Experimental Analysis ◽  
Automatic Generation ◽  
Learning Objects ◽  
Personalized Recommendation ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Web Resources ◽  
The Web

The emerging need to explore the Web as a learning source allied with the purpose of providing personalized recommendations is a tough task. Considering this scenario, this work presents an approach that combines Semantic Web technologies and bio-inspired algorithms to perform personalized recommendation of Learning Objects (LOs) using local repositories and Web resources. Web resources are retrieved and structured as LOs, which allows for the automatic generation of metadata, minimizing course tutors' work. Experiments were performed to verify which bio-inspired evolutionary algorithm would be most appropriate in this context. Also, discussions regarding the quality of recommendations considering local repositories and Web have been made. Initial experiments evaluating the efficiency of the proposed approach have shown promising results.

scholarly journals Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Andrés García-Floriano ◽  
Ángel Ferreira-Santiago ◽  
Cornelio Yáñez-Márquez ◽  
Oscar Camacho-Nieto ◽  
Mario Aldape-Pérez ◽  
...  
Keyword(s):  
Distance Learning ◽  
Learning Experience ◽  
Automatic Generation ◽  
Social Web ◽  
Web Content ◽  
Web Resources ◽  
The Social ◽  
Distance Learning Environment ◽  
Text Content ◽  
Metadata Generation

<p class="3">Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present. As manual metadata generation is time-costly and often eschewed by the authors of the social web resources, automatic generation is a fertile area for research as several kinds of metadata, such as author or topic, can be generated or extracted from the contents of a document. In this paper we propose a novel metadata generation system aimed at automatically tagging distance learning resources. This system is based on a recently-created intelligent pattern classifier; specifically, it trains on a corpus of example documents and then predicts the topic of a new document based on its text content. Metadata is generated in order to achieve a better integration of the web resources with the social networks. Experimental results for a two-class problem are promising and encourage research geared towards applying this method to multiple topics.</p>

The Role of Visual Distractors in the Simon Effect

2017 ◽  
Vol 64 (6) ◽  
pp. 387-397 ◽  
Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà
Keyword(s):  
Simon Effect ◽  
Simon Task ◽  
Automatic Generation ◽  
Spatial Code ◽  
Attentional Model ◽  
Previous Evidence ◽  
Spatial Stimulus ◽  
Attentional Resources ◽  
Code Changes

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

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