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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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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
L S, Davis, S A, Johns, J K, Aggarwal
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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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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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Texture Analysis with Shape Co-occurrence Patterns
2014 22nd International Conference on Pattern Recognition, 2014This paper presents a flexible shape-based texture analysis method by investigating the co-occurrence patterns of shapes. More precisely, a texture image is represented by a tree of shapes, each of which is associated with several attributes. The modeling of texture is thus converted to characterize the tree of shapes. To this aim, we first learn a set
Gang Liu +3 more
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Co-occurrence Analysis Focused on Blogger Communities
2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008We studied the problem of finding a subspace of Web pages that is contextually consistent for co-occurrence analysis. We looked at blogs and proposed blogger-based co-occurrence analysis, which assumes that two items are relevant to each other if they appear in any of the blog entries posted by the same blogger.
Shin-ya Sato +4 more
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Null matrices and the analysis of species co-occurrences
Oecologia, 1998Patterns in species occurrences on islands have been analyzed by several authors. At issue is the number of non-occurring pairs of species (also known as checkerboards). Previous authors have suggested that if the number of checkerboards differs from what is expected by chance, then island communities might have been structured by competition ...
James G, Sanderson +2 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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