Discrete dynamical systems: theory and applications
Discrete dynamical systems: theory and applications
Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Improved algorithms for topic distillation in a hyperlinked environment
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Finding related pages in the World Wide Web
WWW '99 Proceedings of the eighth international conference on World Wide Web
Clustering in large graphs and matrices
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
The stochastic approach for link-structure analysis (SALSA) and the TKC effect
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
What is this page known for? Computing Web page reputations
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Finding authorities and hubs from link structures on the World Wide Web
Proceedings of the 10th international conference on World Wide Web
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Stable algorithms for link analysis
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Learning to Probabilistically Identify Authoritative Documents
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Clustering Categorical Data: An Approach Based on Dynamical Systems
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Link analysis ranking
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Link analysis ranking: algorithms, theory, and experiments
ACM Transactions on Internet Technology (TOIT)
Core algorithms in the CLEVER system
ACM Transactions on Internet Technology (TOIT)
On improving wikipedia search using article quality
Proceedings of the 9th annual ACM international workshop on Web information and data management
Measuring article quality in wikipedia: models and evaluation
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Ranking Links on the Web: Search and Surf Engines
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Less is more: sampling the neighborhood graph makes SALSA better and faster
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Cluster Based Personalized Search
WAW '09 Proceedings of the 6th International Workshop on Algorithms and Models for the Web-Graph
Nonlinear static-rank computation
Proceedings of the 18th ACM conference on Information and knowledge management
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In the recent years there has been a surge of research activity in the area of information retrieval on the World Wide Web, using link analysis of the underlying hypertext graph topology. Most of the algorithms in the literature can be described as dynamical systems, that is, the repetitive application of a function on a set of weights. Algorithms that rely on eigenvector computations, such as HITS and PAGERANK, correspond to linear dynamical systems. In this work we consider two families of link analysis ranking algorithms that no longer enjoy the linearity property of the previous approaches. We study in depth an interesting special case of these two families. We prove that the corresponding non-linear dynamical system converges for any initialization, and we provide a rigorous characterization of the combinatorial properties of the stationary weights. The study of the weights provides a clear and insightful view of the mechanics of the algorithm. We also present extensive experimental results that demonstrate that our algorithm performs well in practice.