Abstract. In this paper we compare our selection based learning algo-rithm with the reinforcement learning algorithm in Web crawlers. The task of the crawlers is to find new information on the Web. We performed simulations based on data collected from the Web. The collected portion of the Web is typical and exhibits scale-free small world (SFSW) struc-ture. We have found that on this SFSW, the weblog update algorithm performs better than the reinforcement learning algorithm. It finds the new information faster than the reinforcement learning algorithm and has better new information/all submitted documents ratio.
We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology appl...
This work addresses issues related to the design and implementation of focused crawlers. Several var...
We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology appl...
Scale-free small world No free lunch theorem Internet The ‘no free lunch theorem ’ claims that f...
International audienceFocused crawling aims at collecting as many Web pages relevant to a target top...
Consider the task of exploring the Web in order to find pages of a particular kind or on a particula...
International audienceWe revisit the Whittle index policy for scheduling web crawlers for ephemeral ...
Consider the task of exploring the Web in order to find pages of a particular kind or on a particula...
In this paper a reinforcement learning methodology for automatic online algorithm selection is intro...
The amount of information over internet has been growing last few years. And it has caused risk of i...
We propose a novel deep web crawling framework based on reinforcement learning. The crawler is regar...
Testing web applications through the GUI can be complex and time-consuming, as it involves checking ...
In recent years, the World Wide Web has shown enormous growth in size. Vast repositories of informat...
In most real-world information processing problems, data is not a free resource. Its acquisition is ...
Summarization: This work addresses issues related to the design and implementation of focused crawle...
We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology appl...
This work addresses issues related to the design and implementation of focused crawlers. Several var...
We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology appl...
Scale-free small world No free lunch theorem Internet The ‘no free lunch theorem ’ claims that f...
International audienceFocused crawling aims at collecting as many Web pages relevant to a target top...
Consider the task of exploring the Web in order to find pages of a particular kind or on a particula...
International audienceWe revisit the Whittle index policy for scheduling web crawlers for ephemeral ...
Consider the task of exploring the Web in order to find pages of a particular kind or on a particula...
In this paper a reinforcement learning methodology for automatic online algorithm selection is intro...
The amount of information over internet has been growing last few years. And it has caused risk of i...
We propose a novel deep web crawling framework based on reinforcement learning. The crawler is regar...
Testing web applications through the GUI can be complex and time-consuming, as it involves checking ...
In recent years, the World Wide Web has shown enormous growth in size. Vast repositories of informat...
In most real-world information processing problems, data is not a free resource. Its acquisition is ...
Summarization: This work addresses issues related to the design and implementation of focused crawle...
We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology appl...
This work addresses issues related to the design and implementation of focused crawlers. Several var...
We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology appl...