TutorBot: An Application AIML based for Web-Learning

O. De Pietro and G. Frontera (Italy)


AIML, Search engine, Artificial Intelligence, e-learning, XML application, natural language, adaptive system, data retrieving.


This paper intends to illustrate the AIML (Artificial Intelligence Markup Language) applicability in the management processes of knowledge bases, with particular attention to the applicability in the contexts of e-learning. For this purpose, the function of a TutorBot planned to be able to support the learners of an e-learning platform; moreover, TutorBot has the possibility, other than that of manipulating direct questions in natural language, to produce researches on the diffused knowledge bases (ex. Internet) through a 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 such purpose the use of a new tag in AIML that allows to manage this specificity is suggested.

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