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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Proceedings ArticleDOI
Ontology ranking based on the analysis of concept structures
TL;DR: The results show that AKTiveRank will have great utility although there is potential for improvement, and a number of metrics are applied in an attempt to investigate their appropriateness for ranking ontologies.
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DrugComboRanker: drug combination discovery based on target network analysis
TL;DR: A novel systematic computational tool DrugComboRanker is proposed to prioritize synergistic drug combinations and uncover their mechanisms of action to reduce drug resistance and improve patients’ outcomes.
Proceedings ArticleDOI
Page Ranking Algorithms: A Survey
TL;DR: A survey of page ranking algorithms and comparison of some important algorithms in context of performance has been carried out.
Proceedings ArticleDOI
On the Vulnerability of Large Graphs
Hanghang Tong,B. Aditya Prakash,Charalampos E. Tsourakakis,Tina Eliassi-Rad,Christos Faloutsos,Duen Horng Chau +5 more
TL;DR: This paper gives the justification behind the choices, and shows that they agree with intuition as well as recent results in immunology, and proposes Net Shield, a fast and scalable algorithm that achieves tremendous speed savings against straightforward competitors.
Journal ArticleDOI
An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification
TL;DR: In this paper, the authors present a survey of kernel-on-graphs (kernels on graphs) and two related similarity matrices, which they refer to as kernels on graph.
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.