acquisition of Web Knowledge by Agents in the context of Human Learning

Web Information may currently be acquired by activating search engines such as Northern Light. However, our daily experience is not only that Web pages are often either redundant or missing but also that there is a mismatch between information needs and the Web' s responses. If we wish to satisfy more complex needs, such as produce Educational material and manage Educational dialogues we need to extract part of the Information and transform it into new interactive documents. The transformation to Knowledge useful for our purposes may either be performed by hand or automatically. In the paper we describe the preliminary choices for our system that will generate local Web pages and their associated interactive processes useful for learning foreign language terminology. Documents and dialogues are designed exploiting domain dependent classification principles (expressed as Abstract Data Types) and Agents. These "autonomous" software modules will be implemented in our own Agent Languages and operate conversationally both as Information seekers and as 1 From http://lcs.www.media.mit.edu/people/foner/Yenta/glossary.html : a definition of serendipitous in an Agent' s glossary: Serendipitous matches Serendipitous matches between users consist of matches made without the user necessarily intending to look for a match. A serendipitous match may involve a user who has not even thought to look for someone with similar interests on some topic, and may be surprised to find that there is any other user out there with such an interest. See also Brian La Macchia' s thesis ( (1) ) about Internet Fishes. See also the on- line Webster dictionary at http://www.m- w.com/cgi- bin/dictionary : Main Entry: ser·en·dip·i·ty; Pronunciation: - ' di- p&- tE; Function: noun; Etymology: from its possession by the heroes of the Persian fairy tale The Three Princes of Serendip; Date: 1754: the faculty or phenomenon of finding valuable or agreeable things not sought for.