A Survey of Eigenvector Methods for Web Information Retrieval

Langville, Amy N.; Meyer, Carl D.

doi:10.1137/s0036144503424786

Cited by 346 publications

(274 citation statements)

References 31 publications

(64 reference statements)

Supporting

Mentioning

255

Contrasting

Unclassified

Order By: Relevance

“…However, the addition of a "personalization" vector [17], such as the query-based similarity vector s 1 on the textual modality [12] would introduce a perturbation towards the results of a text search:…”

Section: Graph-based Fusion In Multimedia Retrievalmentioning

confidence: 99%

Multimedia retrieval based on non-linear graph-based fusion and partial least squares regression

Gialampoukidis

Moumtzidou

Liparas

et al. 2017

Multimed Tools Appl

View full text Add to dashboard Cite

Heterogeneous sources of information, such as images, videos, text and metadata are often used to describe different or complementary views of the same multimedia object, especially in the online news domain and in large annotated image collections. The retrieval of multimedia objects, given a multimodal query, requires the combination of several sources of information in an efficient and scalable way. Towards this direction, we provide a novel unsupervised framework for multimodal fusion of visual and textual similarities, which are based on visual features, visual concepts and textual metadata, integrating non-linear graph-based fusion and Partial Least Squares Regression. The fusion strategy is based on the construction of a multimodal contextual similarity matrix and the non-linear combination of relevance scores from query-based similarity vectors. Our framework can employ more than two modalities and high-level information, without increase in memory complexity, when compared to state-of-the-art baseline methods. The experimental comparison is done in three public multimedia collections in the multimedia retrieval task. The results have shown that the proposed method outperforms the baseline methods, in terms of Mean Average Precision and Precision@20.

show abstract

Section: Graph-based Fusion In Multimedia Retrievalmentioning

confidence: 99%

Multimedia retrieval based on non-linear graph-based fusion and partial least squares regression

Gialampoukidis

Moumtzidou

Liparas

et al. 2017

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…In fact, equation (3) corresponds to the iterative version of the adjusted page rank procedure used by the Google search engine [17]. However, to the best of our knowledge, all such systems consider diffusion processes over adjacency graphs that represent local neighborhoods similar to the way discussed above.…”

Section: Stochastic Diffusion Algorithmmentioning

confidence: 99%

A Probabilistic Diffusion Scheme for Anomaly Detection on Smartphones

Alpcan

Bauckhage

Schmidt

2010

Information Security Theory and Practices. Security and Privacy of Pervasive Systems and Smart Devices

View full text Add to dashboard Cite

Abstract. Widespread use and general purpose computing capabilities of next generation smartphones make them the next big targets of malicious software (malware) and security attacks. Given the battery, computing power, and bandwidth limitations inherent to such mobile devices, detection of malware on them is a research challenge that requires a different approach than the ones used for desktop/laptop computing. We present a novel probabilistic diffusion scheme for detecting anomalies possibly indicating malware which is based on device usage patterns. The relationship between samples of normal behavior and their features are modeled through a bipartite graph which constitutes the basis for the stochastic diffusion process. Subsequently, we establish an indirect similarity measure among sample points. The diffusion kernel derived over the feature space together with the Kullback-Leibler divergence over the sample space provide an anomaly detection algorithm. We demonstrate its applicability in two settings using real world mobile phone data. Initial experiments indicate that the diffusion algorithm outperforms others even under limited training data availability.

show abstract

“…For example, the web ranking and information retrieval [1][2][3], queuing systems [4][5][6][7], stochastic automata networks [8,9], manufacturing systems and inventory control [10] and communication systems [11,12] and so on. In order to analyze their performance measures, it is required to find their stationary probability distributions π by solving the linear system 0, 0, 1, For a finite irreducible and aperiodic Markov chain, there exists a unique stationary probability distribution π whose elements are strictly greater than zero; see, e.g., [13,14].…”

Section: Introductionmentioning

confidence: 99%

An Accelerated Two-level Multigrid Method for Markov Chains

2015

J Appl Computat Math

View full text Add to dashboard Cite

Based on the quadratic extrapolation method and its generalization, this paper presents an accelerated two-level multigrid method for speeding up the numerical computation of the stationary probability vector of an irreducible Markov chain. It shows how to combine these vector extrapolation methods with the two-level multigrid method on the coarse level in detail. Numerical results on two Markov chain problems are provided to illustrate the effectiveness of our proposed method in terms of reducing the iteration counts and computing time.

show abstract

A Survey of Eigenvector Methods for Web Information Retrieval

Cited by 346 publications

References 31 publications

Multimedia retrieval based on non-linear graph-based fusion and partial least squares regression

Multimedia retrieval based on non-linear graph-based fusion and partial least squares regression

A Probabilistic Diffusion Scheme for Anomaly Detection on Smartphones

An Accelerated Two-level Multigrid Method for Markov Chains

Contact Info

Product

Resources

About