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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Search on the Semantic Web
TL;DR: To help human users and software agents find relevant knowledge on theSemantic Web, the Swoogle search engine discovers, indexes, and analyzes the ontologies and facts that are encoded in Semantic Web documents.
Investigations into Trust for Collaborative Information Repositories: A Wikipedia Case Study
Deborah L. McGuinness,Honglei Zeng,Paulo Pinheiro da Silva,Li Ding,Dhyanesh Narayanan,Mayukh Bhaowal +5 more
TL;DR: This paper describes the initial investigations into designing and implementing an extensible trust management layer for collaborative and/or aggregated repositories of information, and presents a trust computation algorithm with experimental results.
Journal ArticleDOI
Discrete Time Markov Chains with R
TL;DR: The markovchain package aims to provide S4 classes and methods to easily handle Discrete Time Markov Chains (DTMCs), filling the gap with what is currently available in the CRAN repository, and an exhaustive description of the main functions included in the package is provided.
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Web Crawler: A Review
TL;DR: The applicability of Web Crawler in the field of web search and a review on Web crawler to different problem domains in web search is discussed.
Journal ArticleDOI
Evaluating journal quality: A review of journal citation indicators and ranking in business and management
John Mingers,Liying Yang +1 more
TL;DR: In this article, the authors evaluate several new indicators, such as the h-index, SJR, SNIP and the Eigenfactor, and conclude that no one indicator is superior but that the H-index and SNIP may be the most effective at the moment.
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.