# Research Papers Google Search Engines Searching

Terrence A. Brooks writes a paper about how search engines are changing the way we understand the world around us.

Top: Computers: Internet: Searching: Search Engines: Google:

**Research Papers**

- Papers by Googlers - Google supplies a partial list of papers written by people now at Google.
- Detecting Colluders in PageRank - PhD thesis by Kahn Mason on methods of discovering groups of websites that collude to boost their reputations, distorting the results of the PageRank algorithm. Stanford University.[PDF]
- Finding Near-replicas of Documents on the Web - By Narayanan Shivakumar and Hector Garcia-Molina. Available google in Postscript research papers format.
- The PageRank Citation Ranking: Bringing Order to the Web - Stanford paper by Lawrence Page, Sergey Brin, Rajeev Motwani, and research papers Terry Winograd, describing PageRank as a static ranking, performed at research papers indexing time, which interprets a link as a vote. Available research papers in Postscript, PDF, and plain text formats.
- An Analysis of Factors Used in Search Engine Ranking - Investigates the influence of different page features on the ranking of Google search engine results.[PDF]
- PageRank Calculation Techniques - Paper by T. Haveliwala, describing efficient techniques for computing PageRank.[PDF]
- Exploiting the Block Structure of the Web for Computing PageRank - This paper by Sepandar Kamvar, Taher Haveliwala, Chris google Manning, and google Gene Golub presents an algorithm to google vastly speed up the google computation of PageRank.[PDF]
- WWW2003: Detecting Near-replicas on the Web by Content and Hyperlink Analysis - Paper by Ernesto Di Iorio, et. al. proposing a technique research papers for finding lists of similar documents, based on a pair research papers of signatures which take into account both the document contents research papers and the hyperlink structure.
- Extrapolation Methods for Accelerating PageRank Computations - This paper by Sepandar Kamvar, Taher Haveliwala, Chris search engines Manning, and Gene Golub, published in WWW13, presents search engines an algorithm to speed up the computation of search engines PageRank by making some initial approximations.[PDF]
- Extracting Patterns and Relations from the World Wide Web - Paper by Sergey Brin presenting a technique which exploits the duality between sets of patterns and relations to grow the target relation, starting from a small sample.[PDF]
- An Analytical Comparison of Approaches to Personalizing PageRank - Taher H. Haveliwala, Sepandar D. Kamvar, and Glen Jeh compare search engines three approaches to personaliizing PageRank.[PDF]
- United States Patent: 6,526,440 - Ranking search results by reranking the results based search engines on research papers local inter-connectivity. Inventor Krishna Bharat; assignee Google.
- The Nature of Meaning in the Age of Google - Terrence A. Brooks writes a paper about how search engines are changing the way we understand the world around us.
- A Case Study in Web Search using TREC Algorithms - Paper from WWW10 by Google employees Amit Singhal research papers and Marcin Kaszkiel.
- The Second Eigenvalue of the Google Matrix - This paper by Sepandar Kamvar and Taher Haveliwala research papers proves google analytically the second eigenvalue of the Google research papers Matrix, which google has implications for the PageRank algorithm.[PDF]
- The Anatomy of a Large-Scale Hypertextual Web Search Engine - The definitive paper by Sergey Brin and Lawrence search engines Page research papers describing PageRank, the algorithm that was later search engines incorporated into research papers the Google search engine.
- Topic-Sensitive PageRank - Taher H. Haveliwala\\'s paper for the 11th International World Wide Web Conference explains that Google proposes to make PageRank reflect importance with respect to a particular topic.
- Method for Node Ranking in a Linked Database - United States Patent 7,058,628, granted to Lawrence Page, which incorporates material from two earlier patents relating to the PageRank system used by Google.
- Dynamic Data Mining: Exploring Large Rule Spaces by Sampling - Paper by Sergey Brin and Lawrence Page, available in Postscript, PDF, and plain text formats.
- Adaptive Methods for the Computation of PageRank - This paper by Sepandar Kamvar, Taher Haveliwala, and search engines Gene search engines Golub describes an algorithm to speed up search engines the computation search engines of PageRank using the fact that search engines pages converge at search engines different rates.[PDF]
- Computing Iceberg Queries Efficiently - Paper by Min Fang, Narayanan Shivakumar, Hector Garcia-Molina, research papers Rajeev Motwani, and Jeffrey D. Ullman, developing research papers efficient execution strategies for a class of queries research papers which perform an aggregate function over an research papers attribute (or set of attributes) and then[PDF]
- Building a Distributed Full-Text Index for the Web - Paper from WWW10 by Sergey Melnik, Sriram Raghavan, search engines Beverly google Yang, Hector Garcia-Molina from the Computer Science search engines Department at google Stanford University.
- Efficient Crawling Through URL Ordering - Paper by Junghoo Cho, Hector Garcia-Molina, and Lawrence Page. Available search engines in Postscript, PDF, and plain text formats. [PDF]

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