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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Journal ArticleDOI
A unified probabilistic framework for Web page scoring systems
TL;DR: This work proposes a general probabilistic framework for Web page scoring systems (WPSS), which incorporates and extends many of the relevant models proposed in the literature and introduces scoring systems for both generic (horizontal) and focused (vertical) search engines.
Proceedings ArticleDOI
Summarizing local context to personalize global web search
TL;DR: This paper investigates the opportunities to select personalized query expansion terms for web search using three different desktop oriented approaches: summarizing the entire desktop data, summarizing only the desktop documents relevant to each user query, and applying natural language processing techniques to extract dispersive lexical compounds from relevant desktop resources.
Journal ArticleDOI
Block models and personalized PageRank.
TL;DR: A principled framework for evaluating ranking methods by studying seed set expansion applied to the stochastic block model is developed and the optimal gradient is derived, surprisingly, that under reasonable assumptions the gradient is asymptotically equivalent to personalized PageRank for a specific choice of the PageRank parameter α that depends on the block model parameters.
Posted Content
Message Passing Algorithms for Sparse Network Alignment
TL;DR: A new message passing algorithm is proposed that allows us to compute, very efficiently, approximate solutions to the sparse network alignment problems with graph sizes as large as hundreds of thousands of vertices.
Journal ArticleDOI
The sensitivity of respondent-driven sampling
TL;DR: For many groups, however, there is no list of members from which to draw a random sample as discussed by the authors, which makes it difficult to make inferences from individuals to larger groups.
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.