Results 11 to 20 of about 796,452 (265)
Macrostate data clustering [PDF]
Physical Review E, 2003 We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable macroscopic states (macrostates) of a diffusive system.
Korenblum, Daniel, Shalloway, David
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Applied Sciences, 2022 Cities are considered complex and open environments with multidimensional aspects including urban forms, urban imagery, and urban energy performance.
Chenyi Cai, Mohamed Zaghloul, Biao Li
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Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design
Sensors, 2023 In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in different ...
Hugo Wai Leung Mak +2 more
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K-RBBSO Algorithm: A Result-Based Stochastic Search Algorithm in Big Data
Applied Sciences, 2022 Clustering is widely used in client-facing businesses to categorize their customer base and deliver personalized services. This study proposes an algorithm to stochastically search for an optimum solution based on the outcomes of a data clustering ...
Sungjin Park, Sangkyun Kim
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Modern Business Data Analysis and Data Visualization: A Real-Time Fusion Study [PDF]
ITM Web of Conferences, 2023 In contemporary data science and analytics, data clustering is a small bucket that divides computation among various child nodes. The network’s capacity, specialized tools, and applications that cannot be trained quickly are among these methods ...
Priya J Suji +3 more
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Clustering Transactional Data [PDF]
, 2002 In this paper we present a partitioning method capable to manage transactions, namelyt uples of variable size of categorical data. We adapt the standard definition of mathematical distance used in the KMeans algorithm to represent dissimilarityam ong transactions, and redefine the notion of cluster centroid.
Giannotti F, Gozzi C, Manco G
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Histogram-based Feature Extraction for GPS Trajectory Clustering [PDF]
EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 2020 Clustering trajectories from GPS data is a crucial task for developing applications in intelligent transportation systems.Most existing approaches perform clustering on raw data consisting of series of GPS positions of moving objects overtime.
Chi Nguyen +4 more
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Application of Multivariate-Rank-Based Techniques in Clustering of Big Data
Vikalpa, 2018 Executive Summary Very large or complex data sets, which are difficult to process or analyse using traditional data handling techniques, are usually referred to as big data.
Pritha Guha
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Proceedings of the 7th International Conference on Data Science, Technology and Applications, 2018 abstract
Michele Ianni +3 more
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Stochastic Data Clustering [PDF]
SIAM Journal on Matrix Analysis and Applications, 2012 In 1961 Herbert Simon and Albert Ando published the theory behind the long-term behavior of a dynamical system that can be described by a nearly uncoupled matrix. Over the past fifty years this theory has been used in a variety of contexts, including queueing theory, brain organization, and ecology.
Carl Dean Meyer, Charles D. Wessell
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