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Open AccessProceedings Article

The PageRank Citation Ranking : Bringing Order to the Web

Lawrence Page, +3 more
- Vol. 98, pp 161-172
TLDR
This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.
Abstract
The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.

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Citations
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Journal ArticleDOI

The predictive power of ranking systems in association football

TL;DR: An overview and comparison of predictive capabilities of several methods for ranking association football teams and the best performing algorithm is a version of the famous Elo rating system that originates from chess player ratings, but several other methods provide better predictive performance than the official ranking method.
Proceedings ArticleDOI

Graph structure in the web --- revisited: a trick of the heavy tail

TL;DR: A large, publicly accessible crawl of the web that was gathered by the Common Crawl Foundation in 2012 and that contains over 3.5 billion web pages and 128.7 billion links is described and analysed, confirming the existence of a giant strongly connected component and providing for the first time accurate measurement of distance-based features, using recently introduced algorithms that scale to the size of the crawl.
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Fast PageRank Computation Via a Sparse Linear System

TL;DR: In this paper, the PageRank computation in the original random surfer model is transformed in the problem of computing the solution of a sparse linear system, and the sparsity of the obtained linear system makes it possible to exploit the effectiveness of the Markov chain index reordering.
Journal ArticleDOI

Integration strategies of multi-omics data for machine learning analysis.

TL;DR: In this article, the authors focus on challenges and existing multi-omics integration strategies by paying special attention to machine learning applications and summarize the most recent data integration methods/ frameworks into five different integration strategies: early, mixed, intermediate, late and hierarchical.
Proceedings ArticleDOI

GraphQ: Scalable PIM-Based Graph Processing

TL;DR: GraphQ, an improved PIM-based graph processing architecture over recent architecture Tesseract, that fundamentally eliminates irregular data movements is proposed and it is shown that increasing memory size in PIM also proportionally increases compute capability.
References
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Journal Article

The Anatomy of a Large-Scale Hypertextual Web Search Engine.

Sergey Brin, +1 more
- 01 Jan 1998 - 
TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.
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Efficient crawling through URL ordering

TL;DR: In this paper, the authors study in what order a crawler should visit the URLs it has seen, in order to obtain more "important" pages first, and they show that a good ordering scheme can obtain important pages significantly faster than one without.
Proceedings ArticleDOI

Silk from a sow's ear: extracting usable structures from the Web

TL;DR: This paper presents the exploration into techniques that utilize both the topology and textual similarity between items as well as usage data collected by servers and page meta-information lke title and size.
Proceedings ArticleDOI

HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering

TL;DR: Experience with HyPursuit suggests that abstraction functions based on hypertext clustering can be used to construct meaningful and scalable cluster hierarchies, and is encouraged by preliminary results on clustering based on both document contents and hyperlink structures.
Journal ArticleDOI

The quest for correct information on the Web: hyper search engines

TL;DR: This paper presents a novel method to extract from a web object its “hyper” informative content, in contrast with current search engines, which only deal with the “textual’ informative content.