17 research outputs found
Descubrimiento automático de mappings en un caso de uso real con altas exigencias de certeza
Los sistemas de integración de información resuelven las diferencias entre las fuentes, en la mayoría de los casos, mediante la creación de mappings, puentes semánticos entre los elementos de las fuentes. Hasta ahora se han propuesto comparadores para generar un conjunto de mappings para cada par de elementos de las fuentes a integrar, y se han realizado estudios experimentales con ellos. El valor añadido del presente trabajo frente a los trabajos experimentales anteriores es que se ha llevado a cabo en un caso real embebido en una aplicación real (en el dominio geográfico) con altas exigencias de certeza
Enhancing Free-text Interactions in a Communication Skills Learning Environment
Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs
Multimedia Development of English Vocabulary Learning in Primary School
In this paper, we describe a prototype of web-based intelligent handwriting education
system for autonomous learning of Bengali characters. Bengali language is used by more than
211 million people of India and Bangladesh. Due to the socio-economical limitation, all of the
population does not have the chance to go to school. This research project was aimed to develop
an intelligent Bengali handwriting education system. As an intelligent tutor, the system can
automatically check the handwriting errors, such as stroke production errors, stroke sequence
errors, stroke relationship errors and immediately provide a feedback to the students to correct
themselves. Our proposed system can be accessed from smartphone or iPhone that allows
students to do practice their Bengali handwriting at anytime and anywhere. Bengali is a
multi-stroke input characters with extremely long cursive shaped where it has stroke order
variability and stroke direction variability. Due to this structural limitation, recognition speed is
a crucial issue to apply traditional online handwriting recognition algorithm for Bengali
language learning. In this work, we have adopted hierarchical recognition approach to improve
the recognition speed that makes our system adaptable for web-based language learning. We
applied writing speed free recognition methodology together with hierarchical recognition
algorithm. It ensured the learning of all aged population, especially for children and older
national. The experimental results showed that our proposed hierarchical recognition algorithm
can provide higher accuracy than traditional multi-stroke recognition algorithm with more
writing variability