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M. Holschneider,
R. Kronland-Martinet,
J. Morlet,
and P. Tchamitchian.
Wavelets, Time-Frequency Methods and Phase Space,
pages 289--297.
Berlin,
1989.
Keywords:
Wavelets,
Multiscale Analysis.
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James F. Allen and P. J. Hayes.
Moments and points in an interval-based temporal logic.
CI,
5(4):225--238,
1989.
Keywords:
Temporal Reasoning.
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Peter Clark and Tim Niblett.
The CN2 induction algorithm.
ML,
3:262--283,
1989.
Keywords:
Noise Handling,
Classification,
Decision Trees.
| Abstract: |
Systems for inducing concept descriptions from examples are valuable tools for assisting in the task of knowledge acquisition for expert systems. This paper presents a description and empirical evaluation of a new induction system, CN2, designed for the efficient induction of simple, comprehensible production rules in domains where problems of poor description language and/or noise may be present. Implementations of the CN2, ID3, and AQ algorithms are compared on three medical classification tasks. |
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Isak Gath and Amir B. Geva.
Unsupervised Optimal Fuzzy Clustering.
TPAMI,
11(7):773-781,
1989.
Keywords:
Classification,
Clustering,
Cluster Validity Measures,
Fuzzy Clustering,
Fuzzy c-Means.
| Abstract: |
Many algorithms for fuzzy clustering depend on initial classes of cluster prototypes, and on assumptions made as to the number of subgroups present in the data. This study reports on a method for carrying out fuzzy classification without a priori assumptions on the number of clusters in the data set. Assessment of cluster validity is based on performance measures using hypervolume and density criterions. The new algorithm is derived from a combination of the fuzzy c-means algorithm and the fuzzymaximum likelihood estimation (FMLE). The UFP-ONC (unsupervised fuzzy partition - optimal number of classes) algorithm performs well in situations of large variability in cluster shapes, densities, and number of data points in each cluster. It has been tested on a number of simulated and real data sets. |
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Stephane G. Mallat.
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation.
TPAMI,
11(7):674--693,
1989.
Keywords:
Wavelets,
Image Data.
| Abstract: |
Multiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolution $2^{j+1}$ and $2^j$ can be extracted by decomposing this signal on a wavelet orthonormal basis of $L^2(\RR^n)$. In $L^2(\RR)$, a wavelet orthonormal basis is a family of functions $(\sqrt{2^j} \varphi(2^jx -n))_{(j,n)\in\ZZ^2}$, which is built by dilating and translating a unique function $\varphi(x)$. This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. For images, the wavelet representation differentiates several spatial orientations. We study the application of this representation to data compression in image coding, texture discrimination and fractal analysis. |
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Sheila A. McIlraith.
Qualitative data modeling: application of a mechanism for interpreting graphical data.
CI,
5:111--120,
1989.
Keywords:
Artificial Intelligence.
| Abstract: |
This paper describes a qualitative technique for interpreting graphical data. Given a set of numerical observations regarding the behaviour of a system, its attributes can be determined by plotting the data and qualitatively comparing the shape of the resulting graph with graphs of system behaviour models. Qualitative data modeling incorporates techniques from pattern recognition and qualitative reasoning to characterize observed data, generate hypothetical interpretations, and select models that best fit the shape of the data. Domain-specific knowledge may be used to substantiate or refuse the likelihood of hypothesized interpretations. The basic data modeling technique is domain independent and is applicable to a wide range of problems. It is illustrated here in the context of a knowledge-based system for well test interpretation. |
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Norman Ramsey.
Literate programming: Weaving a language-independent WEB.
Communications of the ACM,
32(9):1051--1055,
1989.
Keywords:
Literate Programming.
|