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
More filters
Patent
System and method for context-based knowledge search, tagging, collaboration, management and advertisement
TL;DR: In this paper, the authors describe methods and systems for creating, managing, searching, personalizing, and monetizing a knowledge system defined over a corpus of digital content, in which a user can initiate in-depth searches of subject matter and can browse, navigate, pinpoint, and select relevant contexts, concepts, and documents to gain knowledge.
Journal ArticleDOI
Distributed data management using MapReduce
TL;DR: This article aims to provide a comprehensive review of a wide range of proposals and systems that focusing fundamentally on the support of distributed data management and processing using the MapReduce framework.
Book ChapterDOI
Evolving the web into a global data space
TL;DR: This talk will discuss how the openness and self-descriptiveness of Linked Data provide for splitting data integration costs between data publishers, data consumers and third parties and thus might enable global-scale data integration in an evolutionary, pay-as-yougo fashion.
Posted Content
Variations of the Similarity Function of TextRank for Automated Summarization
TL;DR: New alternatives to the similarity function for the TextRank algorithm for automatic summarization of texts achieve a significative improvement using the same metrics and dataset as the original publication.
Proceedings ArticleDOI
MailRank: using ranking for spam detection
TL;DR: This paper investigates the feasibility of MailRank, a new email ranking and classification scheme exploiting the social communication network created via email interactions and shows that MailRank is highly resistant against spammer attacks.
References
More filters
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.