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Engineering Construction and Architectural Management, 2022
PurposeThis study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to ...
Xianbo Zhao
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PurposeThis study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to ...
Xianbo Zhao
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Improving the Keyword Co-occurrence Analysis: An Integrated Semantic Similarity Approach
IEEE International Conference on Industrial Engineering and Engineering Management, 2021Bibliometric studies help yield useful information about the quantity and quality of research works in a particular academic domain. We used the popular bibliometric technique of co-occurrence analysis to explore emergent topical areas in the field of ...
Atanu Bhuyan, Kamal Sanguri, H. Sharma
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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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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 network analysis of modern Chinese poems
Physica A: Statistical Mechanics and its Applications, 2015Abstract A total of 606 co-occurrence networks of Chinese characters and words are constructed from rhymes, free verses, and prose poems. It is found that 98.5 % of networks have scale-free properties, while 19.8 % of networks do not have small-world features, especially the clustering coefficients in 5.6 % of networks are zero ...
Wei Liang +3 more
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Communication Teacher
Courses Communication Research Methods, Qualitative Research Methods. Objectives This activity provides students with an experiential understanding of conducting reflexive thematic analysis in six steps: (1) understanding the data, (2) generating codes, (
Haley Nolan-Cody +2 more
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Courses Communication Research Methods, Qualitative Research Methods. Objectives This activity provides students with an experiential understanding of conducting reflexive thematic analysis in six steps: (1) understanding the data, (2) generating codes, (
Haley Nolan-Cody +2 more
semanticscholar +1 more source
Semantic and Spatial Co-Occurrence Analysis on Object Pairs for Urban Scene Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018Urban scene classifications with very-high-resolution (VHR) satellite images play an important role in urban functional-zone investigation and landscape analysis.
Xiuyuan Zhang, S. Du, Y. Zhang
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