TutorBot: An Application AIML-based for Web-Learning

O. De Pietro and G. Frontera


AIML, search engine, artificial intelligence, e-learning, XML application, natural language, adaptive system, data retrieving


This article illustrates the applicability of AIML (Artificial Intelligence Markup Language) in the management processes of knowledge bases, with particular attention to applicability in the contexts of e-learning. For this purpose, the authors discuss a TutorBot planned to be able to support the learners of an e-learning platform; moreover, TutorBot has the possibility, aside from manipulating direct questions in natural language, to produce research on the diffused knowledge bases (e.g., the Internet) through direct interaction with a search engine. Finally, the management problem in AIML of retrieving information of TutorBot is faced in the interaction with the search engine; to this purpose, the authors suggest a new tag used in AIML that allows for management of this specificity.

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