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Research_Papers resources

United States Patent: 6,526,440

Ranking search results by reranking the results based on 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.

Computing Iceberg Queries Efficiently

Paper by Min Fang, Narayanan Shivakumar, Hector Garcia-Molina, Rajeev Motwani, and Jeffrey D. Ullman, developing efficient execution strategies for a class of queries which perform an aggregate function over an attribute (or set of attributes) and then eliminates aggregate values that are below some specified threshold.

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.

PageRank Calculation Techniques

Paper by T. Haveliwala, describing efficient techniques for computing PageRank.

An Analysis of Factors Used in Search Engine Ranking

Investigates the influence of different page features on the ranking of Google search engine results.

The Anatomy of a Large-Scale Hypertextual Web Search Engine

The definitive paper by Sergey Brin and Lawrence Page describing PageRank, the algorithm that was later incorporated into the Google search engine.

Finding Near-replicas of Documents on the Web

By Narayanan Shivakumar and Hector Garcia-Molina. Available in Postscript format.

Google Research: Publication Database

Supplies a partial list of papers written by people now at Google.

The PageRank Citation Ranking: Bringing Order to the Web

Stanford paper by Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd, describing PageRank as a static ranking, performed at indexing time, which interprets a link as a vote. Available in Postscript, PDF, and plain text formats.

Efficient Crawling Through URL Ordering

Paper by Junghoo Cho, Hector Garcia-Molina, and Lawrence Page. Available in Postscript, PDF, and plain text formats. [PDF]

Dynamic Data Mining: Exploring Large Rule Spaces by Sampling

Paper by Sergey Brin and Lawrence Page, available in Postscript, PDF, and plain text formats.

Google's Pagerank Explained

Paper by Phil Craven, in which he provides theories on how PR is calculated and the importance of internal, dangling, inbound, and outbound links. With PR calculator.

Empirical Analysis of Google SafeSearch

Results of research conducted by Benjamin Edelman of the Berkman Center for Internet and Society, Harvard Law School.

The Google File System

Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung describe the scalable distributed file system that they designed and implemented for Google.

Detecting Near-replicas on the Web by Content and Hyperlink Analysis

Paper by Ernesto Di Iorio, et. al. proposing a technique for finding lists of similar documents, based on a pair of signatures which take into account both the document contents and the hyperlink structure.

Building a Distributed Full-Text Index for the Web

Paper by Sergey Melnik, Sriram Raghavan, Beverly Yang, Hector Garcia-Molina from the Computer Science Department at Stanford University.