Domain-specic internet portals are growing in popularity because they gather content from the Web and organize it for easy access, retrieval and search. For example, allows complex queries by age, location, cost and specialty over summer camps. This functionality is not possible with general, Web-wide search engines. Unfortunately these portals are di cult and time-consuming to maintain. This paper advocates the use of machine learning techniques to greatly automate the creation and maintenance of domain-specic Internet portals. We describe new research in reinforcement learning, information extraction and text classication that enables e cient spidering, the identication of informative text segments, and the population of topic hierarchies. Using these techniques, we have.
