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Janos Haits

The Anatomy of a Search Engine - 1 views

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    In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at ..
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DeeperInsidePR.pdf (application/pdf Object) - 0 views

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    This paper serves as a companion or extension to the "Inside PageRank" paper by Bianchini et al. [19]. It is a comprehensive survey of all issues associated with PageRank, covering the basic PageRank model, available and recommended solution methods, storage issues, existence, uniqueness, and convergence properties, possible alterations to the basic model, suggested alternatives to the traditional solution methods, sensitivity and conditioning, and finally the updating problem. We introduce a few new results, provide an extensive reference list, and speculate about exciting areas of future research.
Janos Haits

Google Research Publication: BigTable - 0 views

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    Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). Despite these varied demands, Bigtable has successfully provided a flexible, high-performance solution for all of these Google products.
Janos Haits

Illuminate - 1 views

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    "Turn academic papers into AI-generated audio discussions About this experiment Illuminate is an experimental technology that uses AI to adapt content to your learning preferences."
Janos Haits

Magenta - 0 views

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    "Magenta is a Google Brain project to ask and answer the questions, "Can we use machine learning to create compelling art and music? If so, how? If not, why not?" Our work is done in TensorFlow, and we regularly release our models and tools in open source. These are accompanied by demos, tutorial blog postings and technical papers. To follow our progress, watch our GitHub and join our discussion group."
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