Focused Crawling Using Temporal Difference-Learning

摘要

This paper deals with the problem of constructing an intelligent Focused Crawler, i.e. a system that is able to retrieve documents of a specific topic from the Web. The crawler must contain a component which assigns visiting priorities to the links, by estimating the probability of leading to a relevant page in the future. Reinforcement Learning was chosen as a method that fits this task nicely, as it provides a method for rewarding intermediate states to the goal. Initial results show that a crawler trained with Reinforcement Learning is able to retrieve relevant documents after a small number of steps.