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 complex network approach to text summarization
TL;DR: A set of 14 summarizers are developed, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores to select sentences for an extractive summary of texts.
Journal ArticleDOI
Compact representation of Web graphs with extended functionality
TL;DR: The k^2-tree is presented, a novel Web graph representation based on a compact tree structure that takes advantage of large empty areas of the adjacency matrix of the graph and offers the least space usage while supporting fast navigation to predecessors and successors and sharply outperforming the others on the extended queries.
Proceedings Article
Identifying Key Users in Online Social Networks: A PageRank Based Approach
TL;DR: A novel PageRank based approach bringing together both research streams for the identification of key users in online social networks merging concepts and findings from research on users' connectivity and communication activity is proposed.
Journal ArticleDOI
BiRank: Towards Ranking on Bipartite Graphs
TL;DR: BiRank as mentioned in this paper is a ranking algorithm for bipartite graphs, which iteratively assigns scores to vertices and finally converges to a unique stationary ranking, which smooths the graph under the guidance of the query vector.
Journal ArticleDOI
Customer churn prediction in telecom using machine learning in big data platform
TL;DR: This work develops a churn prediction model which assists telecom operators to predict customers who are most likely subject to churn and builds a new way of features’ engineering and selection on big data platform.
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.