Searching the Web

By Arvind Arasu, Junghoo Cho, Hector Garcia-Molina, Andreas Paepcke, Sriram Raghavan. ACM Trans. Internet Techn., 2001

709 citations recorded by the source corpus.

Subfields: Information Systems, Statistical and Nonlinear Physics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/3cd77aabd738595f6226fbe624db3a648331c73d

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

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In Statistical and Nonlinear Physics

In Signal Processing

Citations in the corpus

Adversarial Web Search (2011, neutral): “Research Barcelona 08018 Catalunya-Spain chato@yahoo-inc.com Brian D. Davison Lehigh University Bethlehem, PA 18015 USA davison@cse.lehigh.edu Boston – Delft”
DISCOVER: Keyword Search in Relational Databases (2002, background): “[ACGM + 01] offers an overview of current Web search engine design.”
Mining Query Logs: Turning Search Usage Data into Knowledge (2010, background): “Since the advent of web search engines, a large number of papers have been published describing different architectures for search engines, and search engine components [10, 25, 47, 33, 96, 97, 147, 150, 153, 204].”
Efficient query processing in geographic web search engines (2006, neutral): “For background on indexing and query execution in IR and search engines, we refer to [3, 4, 44], and for parallel search architecture to [7, 24, 39].”
UbiCrawler: a scalable fully distributed Web crawler (2004, background): “Indeed, it has been recognized that “as the size of the web grows, it becomes imperative to parallelize the crawling process, in order to finish downloading pages in a reasonable amount of time” [9, 1].”
Deeper Inside PageRank (2004, background): “The excellent survey paper by Arasu et al. [6] also provides a section on storage schemes needed by a Web search engine.”
Detecting near-duplicates for web crawling (2007, background): “Generic crawlers [1, 9] crawl documents and links belonging to a variety of topics, whereas focused crawlers [27, 43, 46] use some specialized knowledge to limit the crawl to pages pertaining to specific topics.”
Winnowing: local algorithms for document fingerprinting (2003, methodology): “For these experiments, we used 500,000 pages downloaded from the Stanford WebBase [1].”
Reinforcement Ranking (2013, background): “As early as 2000, it was observed that 23% of the web pages changed their index daily [1].”
Design and implementation of a high-performance distributed Web crawler (2002, background): “Many researchers have looked at web search technology over the last few years, including crawling strategies, storage, indexing, ranking techniques, and a significant amount of work on the structural analysis of the web and web graph; see [1, 7] for overviews”
Find-similar: similarity browsing as a search tool (2006, background): “7 percent of the queries came from the use of the “more like this” find-similar feature [31, 32].”
Evaluating the use of search engine development tools in IT education (2010, neutral): “For details, please refer to the work of Brin and Page (1998) and Arasu et al. (2001). 1.”
Know your neighbors: web spam detection using the web topology (2007, background): “Research Barcelona 2ISTI CNR C/Ocata 1, 08003 Barcelona Via G. Moruzzi 1, 56124 Pisa Catalunya, SPAIN ITALY ABSTRACT Web spam can signi.cantly deteriorate the quality of search engine results.”
Toward a theory of network gatekeeping: A framework for exploring information control (2008, background): “An information item that is conceived to be newsworthy is less likely to pass gatekeeping – mainly media studies (Shoemaker et al., 2001).”