The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Using PageRank to Characterize Web Structure
COCOON '02 Proceedings of the 8th Annual International Conference on Computing and Combinatorics
Who Links to Whom: Mining Linkage between Web Sites
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Impact of search engines on page popularity
Proceedings of the 13th international conference on World Wide Web
Proceedings of the 13th international conference on World Wide Web
Updating pagerank with iterative aggregation
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
UbiCrawler: a scalable fully distributed web crawler
Software—Practice & Experience
TotalRank: ranking without damping
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Exploiting the hierarchical structure for link analysis
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Distributed PageRank computation based on iterative aggregation-disaggregation methods
Proceedings of the 14th ACM international conference on Information and knowledge management
Convergence Analysis of a PageRank Updating Algorithm by Langville and Meyer
SIAM Journal on Matrix Analysis and Applications
Detecting spam web pages through content analysis
Proceedings of the 15th international conference on World Wide Web
Google's PageRank and Beyond: The Science of Search Engine Rankings
Google's PageRank and Beyond: The Science of Search Engine Rankings
Generalizing PageRank: damping functions for link-based ranking algorithms
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
PageRank: Functional dependencies
ACM Transactions on Information Systems (TOIS)
Challenges in web search engines
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling
Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling
Tracking the random surfer: empirically measured teleportation parameters in PageRank
Proceedings of the 19th international conference on World wide web
Distribution of PageRank mass among principle components of the web
WAW'07 Proceedings of the 5th international conference on Algorithms and models for the web-graph
Site-Based Partitioning and Repartitioning Techniques for Parallel PageRank Computation
IEEE Transactions on Parallel and Distributed Systems
Convergence of multi-level iterative aggregation-disaggregation methods
Journal of Computational and Applied Mathematics
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Research about the topological characteristics of the hyperlink graph has shown that Web possesses a nested block structure, indicative of its innate hierarchical organization. This crucial observation opens the way for new approaches that can usefully regard Web as a Nearly Completely Decomposable(NCD) system; In recent years, such approaches gave birth to various efficient methods and algorithms that exploit NCD from a computational point of view and manage to considerably accelerate the extraction of the PageRank vector. However, very little have been done towards the qualitative exploitation of NCD. In this paper we propose NCDawareRank, a novel ranking method that uses the intuition behind NCD to generalize and refine PageRank. NCDawareRank considers both the link structure and the hierarchical nature of the Web in a way that preserves the mathematically attractive characteristics of PageRank and at the same time manages to successfully resolve many of its known problems, including Web Spamming Susceptibility and Biased Ranking of Newly Emerging Pages. Experimental results show that NCDawareRank is more resistant to direct manipulation, alleviates the problems caused by the sparseness of the link graph and assigns more reasonable ranking scores to newly added pages, while maintaining the ability to be easily implemented on a large-scale and in a computationally efficient manner.