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
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Fake News: A Survey of Research, Detection Methods, and Opportunities.
Xinyi Zhou,Reza Zafarani +1 more
TL;DR: This survey comprehensively and systematically reviews fake news research and identifies and specifies fundamental theories across various disciplines, e.g., psychology and social science, to facilitate and enhance the interdisciplinary research of fake news.
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A further step forward in measuring journals' scientific prestige: The SJR2 indicator
TL;DR: The SJR2 indicator was distributed more equalized than the JIF by Subject Area and almost as equalized as the SNIP, and better than both at the lower level of Specific Subject Areas, and the incorporation of the cosine increased the values of the flows of prestige between thematically close journals.
Proceedings ArticleDOI
Improving web search results using affinity graph
TL;DR: A novel ranking scheme named Affinity Ranking (AR) is proposed to re-rank search results by optimizing two metrics: diversity -- which indicates the variance of topics in a group of documents; and information richness -- which measures the coverage of a single document to its topic.
Journal ArticleDOI
PageRank: standing on the shoulders of giants
TL;DR: The roots of Google's PageRank can be traced back to several early, and equally remarkable, ranking techniques.
Posted Content
Diffusion Improves Graph Learning
TL;DR: This work removes the restriction of using only the direct neighbors by introducing a powerful, yet spatially localized graph convolution: Graph diffusion convolution (GDC), which leverages generalized graph diffusion and alleviates the problem of noisy and often arbitrarily defined edges in real graphs.
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.