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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Inferring Trust Relationships in Web-Based Social Networks
TL;DR: A definition of trust suitable for use in web-based social networks with a discussion of the properties that will influence its use in computation is introduced and two algorithms for inferring trust relationships between individuals that are not directly connected in the network are presented.
Journal ArticleDOI
A Case for Automated Large Scale Semantic Annotation
Stephen Dill,Nadav Eiron,David Gibson,Daniel Gruhl,Ramanathan V. Guha,Anant Jhingran,Tapas Kanungo,Kevin S. McCurley,Sridhar Rajagopalan,Andrew Tomkins,John A. Tomlin,Jason Zien +11 more
TL;DR: It is argued that automated large-scale semantic tagging of ambiguous content can bootstrap and accelerate the creation of the semantic web.
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Analysis of the reputation system and user contributions on a question answering website: StackOverflow
TL;DR: A study of the popular Q&A website StackOverflow, in which users ask and answer questions about software development, algorithms, math and other technical topics, finds that while the majority of questions on the site are asked by low reputation users, on average a high reputation user asks more questions than a user with low reputation.
Posted Content
Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication
TL;DR: This paper proposes a rateless fountain coding strategy that achieves the best of both worlds -- it is proved that its latency is asymptotically equal to ideal load balancing, and it performs asymPTotically zero redundant computations.
Journal ArticleDOI
Categorising social tags to improve folksonomy-based recommendations
TL;DR: A mechanism to automatically filter and classify raw tags in a set of purpose-oriented categories, and shows that content- and context-based tags are considered superior to subjective and organisational tags, achieving equivalent performance to using the whole tag space.
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.
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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.
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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.