Eduardo M. Eisman

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In many of the problems that can be found nowadays, information is scattered across different heterogeneous data sources. Most of the natural language interfaces just focus on a very specific part of the problem (e.g. an interface to a relational database, or an interface to an ontology). However, from the point of view of users, it does not matter where(More)
In this paper we present an embodied conversational agent (ECA) that simulates a real human patient presenting several symptoms for training medical students in the field of primary health care. Students interview the ECA to diagnose his diseases as a doctor would do in a real situation. This virtual patient can communicate using natural language and(More)
The current study aims to obtain knowledge about the nature of the processes involved in Hazard Perception, using measurement techniques to separate and independently quantify these suspected sub-processes: Sensation, Situation Awareness (recognition, location and projection) and decision-making. It applies Signal Detection Theory analysis to Hazard(More)
Recommender systems use a set of reviewers and advice givers with the goal of providing accurate userdependent product predictions. In general, these systems assign weights to different reviewers as a function of their similarity to each user. As products are known to be from different domains, a recommender system also considers product domain information(More)
This paper describes the Multilingual Virtual Simulated Patient framework. It has been created to train the social skills and testing the knowledge of primary health care medical students. The framework generates conversational agents which perform in serveral languages as virtual simulated patients that help to improve the communication and diagnosis(More)