The Google search engine has enjoyed a huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a simple universal ranking algorithm for data lying in the Euclidean space, such as text or image data. The core idea of our method is to rank the data with respect to the intrinsic manifold structure collectively revealed by a great amount of data. Encouraging experimental results from synthetic, image, and text data illustrate the validity of our method
This research is part of the ongoing study to better understand web page ranking on the web. It look...
© The Author(s) 2010. This article is published with open access at Springerlink.com Abstract We pro...
An image search reranking (ISR) technique aims at refining text-based search results by mining image...
The Google search engine has enjoyed a huge success with its web page ranking algorithm, which explo...
The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploit...
Manifold Ranking is a graph-based ranking algorithm be-ing successfully applied to retrieve images f...
Similarity search on the web aims to find web pages similar to a query page and return a ranked list...
Similarity search on the web aims to find web pages similar to a query page and return a ranked list...
This article presents a survey of techniques for ranking results in search engines, with emphasis on...
This paper proposes a novel semi-supervised dimensionality reduction learning algorithm for the rank...
Abstract In recent years, learning on manifolds has attracted much attention in the academia communi...
Query search engines are fundamental tools in locating documents satisfying to Web surfers´ interes...
Contextual information, defined in terms of the proximity of feature vectors in a feature space, has...
How does Google decide which web sites are important? It uses an ingenious algorithm that exploits t...
Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement b...
This research is part of the ongoing study to better understand web page ranking on the web. It look...
© The Author(s) 2010. This article is published with open access at Springerlink.com Abstract We pro...
An image search reranking (ISR) technique aims at refining text-based search results by mining image...
The Google search engine has enjoyed a huge success with its web page ranking algorithm, which explo...
The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploit...
Manifold Ranking is a graph-based ranking algorithm be-ing successfully applied to retrieve images f...
Similarity search on the web aims to find web pages similar to a query page and return a ranked list...
Similarity search on the web aims to find web pages similar to a query page and return a ranked list...
This article presents a survey of techniques for ranking results in search engines, with emphasis on...
This paper proposes a novel semi-supervised dimensionality reduction learning algorithm for the rank...
Abstract In recent years, learning on manifolds has attracted much attention in the academia communi...
Query search engines are fundamental tools in locating documents satisfying to Web surfers´ interes...
Contextual information, defined in terms of the proximity of feature vectors in a feature space, has...
How does Google decide which web sites are important? It uses an ingenious algorithm that exploits t...
Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement b...
This research is part of the ongoing study to better understand web page ranking on the web. It look...
© The Author(s) 2010. This article is published with open access at Springerlink.com Abstract We pro...
An image search reranking (ISR) technique aims at refining text-based search results by mining image...
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