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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

Measuring and moderating opinion polarization in social networks

TL;DR: The polarization index is defined, which, given a network and the opinions of the individuals in the network, it quantifies the polarization observed in theNetwork, and it is proved that both problems are NP-hard.
Patent

Systems and methods for ranking documents based upon structurally interrelated information

TL;DR: The vulnerability of existing ranking algorithms such as PageRank to Web pages that are artificially generated for the sole purpose of inflating the score of target page(s) is addressed as discussed by the authors.
Journal ArticleDOI

Interface methods : renegotiating relations between digital social research, STS and sociology

TL;DR: In this article, a distinctive approach to methods development in digital social research called "interface methods" is introduced, which highlights the dynamism and relative under-determinacy of digital methods, and affirms that multiple methodological traditions intersect in digital devices and research.
Journal ArticleDOI

Edge betweenness centrality: A novel algorithm for QoS-based topology control over wireless sensor networks

TL;DR: EBC is based on the concept of betweenness centrality, which has been first introduced in the context of social network analysis, and measures the ''importance'' of each node in the network, and outperforms the competitor ones in all observed cases.
Proceedings ArticleDOI

Learning latent semantic relations from clickthrough data for query suggestion

TL;DR: This paper develops a novel, effective and efficient two-level query suggestion model by mining clickthrough data, in the form of two bipartite graphs (user-query and query-URL bipartITE graphs) extracted from theclickthrough data.
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.
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.