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Similarity search in high dimensions via hashing

by Aristides Gionis, Piotr Indyk, Rajeev Motwani , 1999
"... The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image dat ..."
Abstract - Cited by 641 (10 self) - Add to MetaCart
The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image

On the Self-similar Nature of Ethernet Traffic (Extended Version)

by Will E. Leland, Murad S. Taqqu, Walter Willinger, Daniel V. Wilson , 1994
"... We demonstrate that Ethernet LAN traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal-like behavior, that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks, and that aggrega ..."
Abstract - Cited by 2213 (46 self) - Add to MetaCart
We demonstrate that Ethernet LAN traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal-like behavior, that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks

Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level

by Walter Willinger, Murad S. Taqqu, Robert Sherman, Daniel V. Wilson - IEEE/ACM TRANSACTIONS ON NETWORKING , 1997
"... A number of recent empirical studies of traffic measurements from a variety of working packet networks have convincingly demonstrated that actual network traffic is self-similar or long-range dependent in nature (i.e., bursty over a wide range of time scales) -- in sharp contrast to commonly made tr ..."
Abstract - Cited by 743 (24 self) - Add to MetaCart
traffic modeling assumptions. In this paper, we provide a plausible physical explanation for the occurrence of self-similarity in LAN traffic. Our explanation is based on new convergence results for processes that exhibit high variability (i.e., infinite variance) and is supported by detailed statistical

Image Quality Assessment: From Error Visibility to Structural Similarity

by Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, Eero P. Simoncelli - IEEE TRANSACTIONS ON IMAGE PROCESSING , 2004
"... Objective methods for assessing perceptual image quality have traditionally attempted to quantify the visibility of errors between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapt ..."
Abstract - Cited by 1499 (114 self) - Add to MetaCart
Objective methods for assessing perceptual image quality have traditionally attempted to quantify the visibility of errors between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly

Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching

by Sergey Melnik, Hector Garcia-molina, Erhard Rahm , 2002
"... Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (sch ..."
Abstract - Cited by 592 (12 self) - Add to MetaCart
illustrate how our matching algorithm is deployed as one of several high-level operators in an implemented testbed for managing information models and mappings.

Automatic Word Sense Discrimination

by Hinrich Schütze - Journal of Computational Linguistics , 1998
"... This paper presents context-group discrimination, a disambiguation algorithm based on clustering. Senses are interpreted as groups (or clusters) of similar contexts of the ambiguous word. Words, contexts, and senses are represented in Word Space, a high-dimensional, real-valued space in which closen ..."
Abstract - Cited by 536 (1 self) - Add to MetaCart
This paper presents context-group discrimination, a disambiguation algorithm based on clustering. Senses are interpreted as groups (or clusters) of similar contexts of the ambiguous word. Words, contexts, and senses are represented in Word Space, a high-dimensional, real-valued space in which

VisualSEEk: a fully automated content-based image query system

by John R. Smith, Shih-fu Chang , 1996
"... We describe a highly functional prototype system for searching by visual features in an image database. The VisualSEEk system is novel in that the user forms the queries by diagramming spatial arrangements of color regions. The system finds the images that contain the most similar arrangements of ..."
Abstract - Cited by 762 (31 self) - Add to MetaCart
We describe a highly functional prototype system for searching by visual features in an image database. The VisualSEEk system is novel in that the user forms the queries by diagramming spatial arrangements of color regions. The system finds the images that contain the most similar arrangements

The CES-D scale: A self-report depression scale for research in the general population

by Lenore Sawyer Radloff - Applied Psychological Measurement , 1977
"... The CES-D scale is a short self-report scale designed to measure depressive symptomatology in the general population. The items of the scale are symptoms associated with depression which have been used in previously validated longer scales. The new scale was tested in household interview surveys and ..."
Abstract - Cited by 2835 (1 self) - Add to MetaCart
and in psychiatric settings. It was found to have very high internal consistency and adequate test-retest repeatability. Validity was established by pat-terns of correlations with other self-report measures, by correlations with clinical ratings of depression, and by relationships with other variables which support

Clustering by passing messages between data points

by Brendan J. Frey, Delbert Dueck - Science , 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
Abstract - Cited by 696 (8 self) - Add to MetaCart
if that initial choice is close to a good solution. We devised a method called “affinity propagation,” which takes as input measures of similarity between pairs of data points. Real-valued messages are exchanged between data points until a high-quality set of exemplars and corresponding clusters gradually emerges

Basic objects in natural categories

by Eleanor Rosch, Carolyn B. Mervis, Wayne D. Gray, David M. Johnson, Penny Boyes-braem - COGNITIVE PSYCHOLOGY , 1976
"... Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest categ ..."
Abstract - Cited by 892 (1 self) - Add to MetaCart
Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest
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