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Co-occurrence analysis of scientific documents in citation networks
International Journal of Knowledge-based and Intelligent Engineering Systems, 2020Citation pattern analysis is an important component for measuring research performance of the author. Co-citation analysis has been used as an effective method to find citation pattern analysis, but it does not take co-occurrence analysis among authors. A method to find co-occurrence analysis among authors is proposed in this work.
Satish Muppidi, K. Thammi Reddy
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Texture Analysis Using Generalized Co-Occurrence Matrices
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979We present a new approach to texture analysis based on the spatial distribution of local features in unsegmented textures. The textures are described using features derived from generalized co-occurrence matrices (GCM). A GCM is determined by a spatial constraint predicate F and a set of local features P = {(Xi, Yi, di), i = 1,..., m} where (Xi, Yi) is
Larry S. Davis +2 more
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About the statistical analysis of co-occurrence
Computers and the Humanities, 1992Various objections are raised against current practice in co-occurrence analysis. The use of Yule's coefficient Y is then advocated.
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Biological Information Extraction and Co-occurrence Analysis
2014Nowadays, it is possible to identify terms corresponding to biological entities within passages in biomedical text corpora: critically, their potential relationships then need to be detected. These relationships are typically detected by co-occurrence analysis, revealing associations between bioentities through their coexistence in single sentences and/
Georgios A, Pavlopoulos +3 more
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Co-occurrence analysis of speech waveforms
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985The co-occurrence matrix, a two-dimensional histogram of pairs of sample amplitudes, is explored as a representation of the digital speech waveform. Co-occurrence matrix representations support a hypothesis-testing approach to digital speech analysis. This approach is pursued in the formulation of a quantitative (chi-square) measure of sample amplitude
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Analysis of co-occurrence in a fungal community
Mycological Research, 1991An approach is presented for quantifying associations between species pairs over a scale of 0·5–1 mm by plating several 0·5–1 mm particles of washed organic matter on agar plates, and observing whether or not fungal species which emerge from the particles are distributed in a random manner with regard to each other. Most of the associations between the
D.A. Wardle, D. Parkinson
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Co-occurrence matrices for image analysis
Electronics & Communication Engineering Journal, 1993The authors present a range of techniques for image segmentation and edge detection based on co-occurrence matrices. Co-occurrence matrices are described and transforms are defined which adapt to global image characteristics and emphasise the differences between typical and atypical image features using co-occurrence matrices as look-up tables.
J.F. Haddon, J.F. Boyce
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Research on Gambling in Young People: A Co-Occurrence Analysis
Journal of Gambling Studies, 2022Gambling as a risk factor in youth development, particularly its causes and consequences, has been the subject of a growing number of studies. However, the literature relating to young people has yet to be compiled in a systematic form. The present study adopts a descriptive bibliometric approach to map global research on gambling in young people using
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Learning Sentiments using Co-occurrence Analysis
2021 Research, Invention, and Innovation Congress: Innovation Electricals and Electronics (RI2C), 2021As part of natural language processing, sentiment analysis intends to investigate the author's emotions while writing a given text. This paper proposes a new method that uses a co-occurrence graph that can be automatically extended in a background reading (and learning) process, when a person's additional text source is available.
Nirach Romyen +3 more
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Generalized co-occurrence matrix for multispectral texture analysis
Proceedings of 13th International Conference on Pattern Recognition, 1996We present a new co-occurrence matrix based approach for multispectral texture analysis. The spectral and spatial domains of the multispectral textures are processed separately. The color space used in this study is represented by subspaces and it is classified by the averaged learning subspace method (ALSM).
Markku Hauta-Kasari +3 more
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