513,915 research outputs found
Artequakt: Generating tailored biographies from automatically annotated fragments from the web
The Artequakt project seeks to automatically generate narrativebiographies of artists from knowledge that has been extracted from the Web and maintained in a knowledge base. An overview of the system architecture is presented here and the three key components of that architecture are explained in detail, namely knowledge extraction, information management and biography construction. Conclusions are drawn from the initial experiences of the project and future progress is detailed
Photon Structure Function
After briefly explaining the idea of photon structure functions (\f2gam\ ,
\flgam) I review the current theoretical and experimental developements in the
subject of extraction of \qvph\ from a study of the Deep Inelastic Scattering
(DIS). I then end by pointing out recent progress in getting information about
the parton content of the photon from hard processes other than DIS.Comment: 14 pages, 6 postscript figures, latex, uses equation.sty and
epsfig.sty .sty files not adde
Randomized Dimensionality Reduction for k-means Clustering
We study the topic of dimensionality reduction for -means clustering.
Dimensionality reduction encompasses the union of two approaches: \emph{feature
selection} and \emph{feature extraction}. A feature selection based algorithm
for -means clustering selects a small subset of the input features and then
applies -means clustering on the selected features. A feature extraction
based algorithm for -means clustering constructs a small set of new
artificial features and then applies -means clustering on the constructed
features. Despite the significance of -means clustering as well as the
wealth of heuristic methods addressing it, provably accurate feature selection
methods for -means clustering are not known. On the other hand, two provably
accurate feature extraction methods for -means clustering are known in the
literature; one is based on random projections and the other is based on the
singular value decomposition (SVD).
This paper makes further progress towards a better understanding of
dimensionality reduction for -means clustering. Namely, we present the first
provably accurate feature selection method for -means clustering and, in
addition, we present two feature extraction methods. The first feature
extraction method is based on random projections and it improves upon the
existing results in terms of time complexity and number of features needed to
be extracted. The second feature extraction method is based on fast approximate
SVD factorizations and it also improves upon the existing results in terms of
time complexity. The proposed algorithms are randomized and provide
constant-factor approximation guarantees with respect to the optimal -means
objective value.Comment: IEEE Transactions on Information Theory, to appea
Investigation related to multispectral imaging systems
A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community
Cosmic X-ray physics
The soft X-ray sky survey data are combined with the results from the UXT sounding rocket payload. Very strong constraints can then be placed on models of the origin of the soft diffuse background. Additional observational constraints force more complicated and realistic models. Significant progress was made in the extraction of more detailed spectral information from the UXT data set. Work was begun on a second generation proportional counter response model. The first flight of the sounding rocket will have a collimator to study the diffuse background
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