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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Proceedings ArticleDOI
Mining structural hole spanners through information diffusion in social networks
Tiancheng Lou,Jie Tang +1 more
TL;DR: This work precisely defines the problem of mining top-k structural hole spanners in large-scale social networks and provides an objective (quality) function to formalize the problem and proposes an efficient algorithm with provable approximation guarantees to solve the problem.
The Eigenfactor Metrics: A network approach to assessing scholarly journals
TL;DR: The Eigenfactor and Article Influence Score use an iterative ranking scheme similar to Google's PageRank algorithm, and with this approach, citations from top journals are weighted more heavily than citations from lower-tier publications.
Journal ArticleDOI
Ranking significance of software components based on use relations
TL;DR: A novel graph-representation model of a software component library (repository) called component rank model is proposed, which shows that SPARS-J gives a higher rank to components that are used more frequently, so software engineers looking for a component have a better chance of finding it quickly.
Proceedings ArticleDOI
Simple Unsupervised Keyphrase Extraction using Sentence Embeddings
TL;DR: This paper tackles keyphrase extraction from single documents with EmbedRank: a novel unsupervised method, that leverages sentence embeddings, that achieves higher F-scores than graph-based state of the art systems on standard datasets and is suitable for real-time processing of large amounts of Web data.
Journal ArticleDOI
Variational Quantum Computation of Excited States
TL;DR: In this article, the authors propose a method to calculate excited state energies of electronic structure Hamiltonians using overlap estimation, which requires the same number of qubits as the variational quantum eigenvalue solver (VQE) and at most twice the circuit depth.
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.