Search Results - subject:"graph clustering"

Analysis of urban functional areas based on graph clustering neural networks

Bai, Huimin; Zhu, Xia; Liu, Yuanping; Zhang, Tiange; … - In: Journal of urban management 14 (2025) 3, pp. 642-656

proposes a method based on Graph Clustering Neural Networks to analyze and study urban functional areas. To begin with, the …-economic characteristics. Through the use of Graph Clustering Neural Networks and clustering algorithms, urban functional areas can be … verified by comparison with real images. Beijing was chosen as the study area for this research. The Graph Clustering Neural …

Persistent link: https://www.econbiz.de/10015458311

Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market

Korniejczuk, Adam; Ślepaczuk, Robert - 2024

Persistent link: https://www.econbiz.de/10014634696

Research on Weibo marketing advertising push method based on social network data mining

Zhang, Yanyan - In: International journal of electronic business : IJEB 19 (2024) 4, pp. 393-406

Persistent link: https://www.econbiz.de/10015412254

Market graph clustering via QUBO and digital annealing

Hong, Seo Woo; Miasnikof, Pierre; Kwon, Roy; Lawryshyn, Yuri - In: Journal of Risk and Financial Management 14 (2021) 1, pp. 1-13

modeling, to formulate the index-tracking problem as a binary quadratic K-medoid graph-clustering problem. Our initial results …

Persistent link: https://www.econbiz.de/10012611592

Market graph clustering via QUBO and digital annealing

Hong, Seo Woo; Miasnikof, Pierre; Kwon, Roy; Lawryshyn, Yuri - In: Journal of risk and financial management : JRFM 14 (2021) 1/34, pp. 1-13

modeling, to formulate the index-tracking problem as a binary quadratic K-medoid graph-clustering problem. Our initial results …

Persistent link: https://www.econbiz.de/10012417719

Adaptive Nonparametric Community Detection

Adamyan, Larisa; Efimov, Kirill; Spokoiny, Vladimir - 2019

Understanding the topological structure of real world networks is of huge interest in a variety of fields. One of the way to investigate this structure is to find the groups of densely connected nodes called communities. This paper presents a new non-parametric method of community detection in...

Persistent link: https://www.econbiz.de/10012433220

Local search for constrained graph clustering in biological networks

Tran, Duy Hoang; Babaki, Behrouz; Van Daele, Dries; … - In: Computers & operations research : and their … 132 (2021), pp. 1-12

Persistent link: https://www.econbiz.de/10012595733

An enhanced MILP-based branch-and-price approach to modularity density maximization on graphs

Sato, Keisuke; Izunaga, Yoichi - In: Computers & operations research : and their … 106 (2019), pp. 236-245

Persistent link: https://www.econbiz.de/10012014417

An Optimal Data Placement Strategy for Improving System Performance of Massive Data Applications Using Graph Clustering

Balasundaram, S. R.; Vengadeswaran, S. - In: International Journal of Ambient Computing and … 9 (2018) 3, pp. 15-30

analyzed for identifying access pattern which is depicted as a graph. Markov clustering, a Graph clustering algorithm is …

Persistent link: https://www.econbiz.de/10012042679

An Approach to Clustering of Text Documents Using Graph Mining Techniques

Mishra, Brojo Kishore; Rao, Bapuji - In: International Journal of Rough Sets and Data Analysis … 4 (2017) 1, pp. 38-55

This paper introduces a new approach of clustering of text documents based on a set of words using graph mining techniques. The proposed approach clusters (groups) those text documents having searched successfully for the given set of words from a set of given text documents. The document-word...

Persistent link: https://www.econbiz.de/10012047371