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Open AccessProceedings Article

The PageRank Citation Ranking : Bringing Order to the Web

Lawrence Page, +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.

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Citations
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Patent

System, method and service for ranking search results using a modular scoring system

TL;DR: Rank aggregation as discussed by the authors is a modular scoring system using rank aggregation that merges search results into an ordered list of results using many different features of documents, such as indegree, page ranking, URL length, proximity to the root server of an intranet, etc.
Proceedings Article

Discourse indicators for content selection in summarization

TL;DR: The results establish the usefulness of discourse features and find that lexical overlap provides a simple and cheap alternative to discourse for computing text structure with comparable performance for the task of content selection.
Journal ArticleDOI

Adding Geographic Scopes to Web Resources

TL;DR: This paper presents work on automatically identifying the geographical scope of web documents, which provides the means to develop retrieval tools that take the geographical context into consideration, and makes extensive use of an ontology of geographical concepts.
Proceedings ArticleDOI

CollabRank: Towards a Collaborative Approach to Single-Document Keyphrase Extraction

TL;DR: This paper proposes a novel approach named CollabRank to collaborative single-document keyphrase extraction by making use of mutual influences of multiple documents within a cluster context, and finds that the system performance relies positively on the quality of document clusters.
Journal ArticleDOI

Whom to ask?: jury selection for decision making tasks on micro-blog services

TL;DR: This paper study the Jury Selection Problem (JSP) by utilizing crowdsourcing for decision making tasks on micro-blog services, and proves the monotonicity of JER on individual error rate and proposes an efficient exact algorithm for JSP.
References
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Journal Article

The Anatomy of a Large-Scale Hypertextual Web Search Engine.

Sergey Brin, +1 more
- 01 Jan 1998 - 
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.