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Analyzing supply chain technology trends through network analysis and clustering techniques: a patent-based study
The supply chain forms the backbone of the modern consumer economy, weaving an intricate network of stakeholders across geographical and...
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Trust-Similarity Analysis-Based Clustering Method
Opinion similarity and trust relationship are considered to be two important measurement attributes for implementing clustering. Traditional...
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Role of land use in China’s urban energy consumption: based on a deep clustering network and decomposition analysis
Land use can affect energy consumption by changing the economic and social structure of cities. Thus, the optimization of land use patterns is key to...
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A Literature Review on Correlation Clustering: Cross-disciplinary Taxonomy with Bibliometric Analysis
The correlation clustering problem identifies clusters in a set of objects when the qualitative information about objects’ mutual similarities or...
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Mitigating the negative effect of intrabrand clustering: the role of interbrand clustering and firm size
Clustering—geographic concentrations of entities—has recently received more attention in marketing research and has been shown to affect multiple...
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Fuzzy clustering of financial time series based on volatility spillovers
In this paper we propose a framework for fuzzy clustering of time series based on directional volatility spillovers. In the case of financial time...
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Trust Cop-Kmeans Clustering Method
Social network large-scale decision-making (SNLSDM) has attracted widespread attention in the field of decision science. Clustering is one of the...
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An Improved Boosting Bald Eagle Search Algorithm with Improved African Vultures Optimization Algorithm for Data Clustering
Data clustering is one of the main issues in the optimization problem. It is the process of clustering a group of items into several groups. Items...
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A novel auto-pruned ensemble clustering via SOCP
Operations Research (OR) plays a crucial role in strategic decision-making in today’s business world; it uses complex algorithms and data analytic to...
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Tail dependence-based fuzzy clustering of financial time series
In this paper, we propose a new fuzzy clustering of time series with entropy regularization. Following a model-based approach, the dissimilarity...
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Geometry-Inference Based Clustering Heuristic: New k-means Metric for Gaussian Data and Experimental Proof of Concept
K-means is one of the algorithms that are most utilized in data clustering; the number of metrics is coupled to k-means to reach reasonable levels of...
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Clustering
This chapter will discuss the unsupervised machine learning technique known as clustering and its main approaches and use cases. After presenting...
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Cub model-based clustering of Likert-type data with a tourist satisfaction application
In investigating customer satisfaction with products or services, the most popular approach still relies on interviews or questionnaires to obtain...
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Data fusion algorithm of wireless sensor network based on clustering and fuzzy logic
In order to reduce network energy consumption and prolong the network lifetime in wireless sensor networks, a data fusion algorithm named CFLDF is...
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Robust asymmetric non-negative matrix factorization for clustering nodes in directed networks
Directed networks appear in an expanding array of applications, for example, the world wide web, social networks, transaction networks, and citation...
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Fuzzy clustering with entropy regularization for interval-valued data with an application to scientific journal citations
In recent years, the research of statistical methods to analyze complex structures of data has increased. In particular, a lot of attention has been...
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Compatibility Distance Oriented Off-Center Clustering Method
Social network large-scale decision-making with probabilistic linguistic information is becoming a hot research topic in the field of decision...
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Two-dimensional polygon classification and pairwise clustering for pairing in ship parts nesting
In the shipbuilding industry, nesting is arranging the cutting patterns of ship parts to increase the utilization rate of steel sheets and reduce the...
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A typology of social innovation: A comparative study of clustering methodologies
This study offers a typology of the Social Innovation (SI) field. A sample of 5,152 documents from the Scopus database is screened using a clustering...
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Problem-driven scenario clustering in stochastic optimization
In stochastic optimisation, the large number of scenarios required to faithfully represent the underlying uncertainty is often a barrier to finding...
