摘要：In our project (GENTA - GENeral belief reTrieving Agent), we are trying to realize a conversational agent, which would be able to talk in any domain by using web-mining techniques to retrieve information that is impossible to obtain in usually used corpora. In our research we try to simulate reasoning processes based on Internet textual resources including chat logs. Our goal is a dialogue system which learns the linguistic behaviour of an interlocutor concentrating on the role of emotion during analysing discourse. The system is not using any databases of commonsensical word descriptions, they are being automatically retrieved from the WWW. We describe two values called Positiveness and Usualness and explain their role in the Inductive Learning that is used for achieving emotion-based reasoning skills. As this is a new approach to knowledge acquisition for dialogue agents we concentrate on the theoretical part of our project. Finally we introduce the results of the preliminary experiments.
关键词：natural language processing; spoken dialog agents; affective computing
