Title :
Text-learning and related intelligent agents: a survey
Author_Institution :
Jozef Stefan Inst., Ljubljana Univ., Slovenia
Abstract :
In surveying current research in the development of text-learning intelligent agents, the author focuses on three key criteria: what representation the particular application uses for documents, how it selects features, and what learning algorithm it uses. She then describes Personal WebWatcher, a content-based intelligent agent that uses text-learning for user-customized Web browsing
Keywords :
feature extraction; information needs; information resources; information retrieval; knowledge representation; learning systems; software agents; Personal WebWatcher; content-based intelligent agent; document representation; feature selection; learning algorithm; text-learning intelligent agents; user-customized Web browsing; Calendars; Computer science; Information retrieval; Intelligent agent; Internet; Machine learning; Marine animals; National electric code; Speech; World Wide Web;
Journal_Title :
Intelligent Systems and their Applications, IEEE
DOI :
10.1109/5254.784084
