For providing quick and accurate results, a search engine maintains a local snapshot of the entire web. And, to keep this local cache fresh, it employs a crawler for tracking changes across various web pages. However, finite bandwidth availability and server restrictions impose some constraints on the crawling frequency. Consequently, the ideal...
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May 18, 2020 (v1)Conference paperUploaded on: December 4, 2022
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December 20, 2021 (v1)Conference paper
A search engine uses a web crawler to crawl the pages from the world wide web (WWW) and aims to maintain its local cache as fresh as possible. Unfortunately, the rates at which different pages change in WWW are highly nonuniform and also, unknown in many real-life scenarios. In addition, the finite available bandwidth and possible server...
Uploaded on: December 3, 2022 -
February 2022 (v1)Journal article
A search engine maintains local copies of different web pages to provide quick search results. This local cache is kept up-to-date by a web crawler that frequently visits these different pages to track changes in them. Ideally, the local copy should be updated as soon as a page changes on the web. However, finite bandwidth availability and...
Uploaded on: December 3, 2022 -
June 5, 2021 (v1)Book section
We analyze the DQN reinforcement learning algorithm as a stochastic approximation scheme using the o.d.e. (for 'ordinary differential equation') approach and point out certain theoretical issues. We then propose a modified scheme called Full Gradient DQN (FG-DQN, for short) that has a sound theoretical basis and compare it with the original...
Uploaded on: December 3, 2022