Open AccessProceedings Article
The PageRank Citation Ranking : Bringing Order to the Web
Lawrence Page,Sergey Brin,Rajeev Motwani,Terry Winograd +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.read more
Citations
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A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy
Guido Caldarelli,Matthieu Cristelli,Andrea Gabrielli,Luciano Pietronero,Antonio Scala,Andrea Tacchella +5 more
TL;DR: This paper defines the country-country and product-product projected networks and introduces a novel method of filtering information based on elements’ similarity, which uncovers a strong non-linear interaction between the diversification of a country and the ubiquity of its products, thus suggesting the possible need of moving towards more efficient and direct non- linear fixpoint algorithms to rank countries and products in the global market.
Proceedings ArticleDOI
Optimal distributed all pairs shortest paths and applications
Stephan Holzer,Roger Wattenhofer +1 more
TL;DR: A new lower bound for approximating the diameter D of a graph is presented: being allowed to answer D+1 or D can speed up the computation by at most a factor D, and an algorithm is provided that achieves such a speedup of D and computes an (1+εepsilon) multiplicative approximation of the diameter.
Journal ArticleDOI
Understanding Graph-Based Trust Evaluation in Online Social Networks: Methodologies and Challenges
TL;DR: This article focuses on graph-based trust evaluation models in OSNs, particularly in the computer science literature, and comparatively reviews two categories of graph-simplification-based and graph-analogy-based approaches and discusses their individual problems and challenges.
Proceedings ArticleDOI
Who will follow you back?: reciprocal relationship prediction
TL;DR: This study provides strong evidence of the existence of the structural balance among reciprocal relationships and proposes a learning framework to formulate the problem of reciprocal relationship prediction into a graphical model that incorporates social theories into a machine learning model.
References
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Journal Article
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Sergey Brin,Lawrence Page +1 more
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.
Journal ArticleDOI
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.