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Community
One of the approaches discussed in Chapter 1, “Approaches,” is community-driven documentation, which refers to a collaborative approach to...
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Exploring temporal community evolution: algorithmic approaches and parallel optimization for dynamic community detection
Dynamic (temporal) graphs are a convenient mathematical abstraction for many practical complex systems including social contacts, business...
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Attribute subspace-guided multi-scale community detection
Community detection is designed to divide a network into multiple subnetworks (communities) with high cohesiveness, which has attracted wide...
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Open Community Communication Channels
In this chapter, I will introduce the topic of Open Community Communication Channels in the context of engineering documentation. Open community...
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Community-Led Growth als Markteintrittsstrategie für Software-Startups im B2B-Umfeld
Community-driven marketing and sales activities have been steadily increasing since the pandemic and are already establishing themselves as...
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Research on Dynamic Community Detection Method Based on Multi-dimensional Feature Information of Community Network
With the continuous development of technology, we have the ability to fully record all aspects of data information of every individual in the...
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Community deception in directed influence networks
Community deception is about protecting users of a community from being discovered by community detection algorithms. This paper studies community...
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An improved label propagation algorithm based on community core node and label importance for community detection in sparse network
Community structure can be used to analyze and understand the structural functions in a network, reveal its implicit information, and predict its...
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PERMDEC: community deception in weighted networks using permanence
Community detection is used to determine the network structure and node relationships. However, it raises privacy concerns when locating and...
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How AI hype impacts the LGBTQ + community
Hype around Artificial Intelligence (AI) has been a feature of this technology since its inception. However, the most recent wave of AI hype has been...
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India’s Conception of Community Data and Addressing Concerns for Access to Justice
This paper discusses the idea of community data that was introduced in the Non-Personal Data framework in India. Our interest is to engage with...
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Predicting properties of nodes via community-aware features
This paper shows how information about the network’s community structure can be used to define node features with high predictive power for...
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Adaptive graph contrastive learning for community detection
Recently, graph contrastive learning (GCL) has received considerable interest in graph representation learning for its robustness in capturing...
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A biased edge enhancement method for truss-based community search
Most truss-based community search methods are usually confronted with the fragmentation issue. We propose a Biased edge Enhancement method for...
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Building Community Service Ecosystem Models
The digital age has led to new resource sharing mechanisms, which require a corresponding adjustment in community governance. Constructing community...
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Innovations for Community Services 24th International Conference, I4CS 2024, Maastricht, The Netherlands, June 12–14, 2024, Proceedings
This book constitutes the refereed proceedings of the 24th International Conference on Innovations for Community Services, I4CS 2024, held in...
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A nonnegative Gumbel-based encoder–decoder approach for community detection
Graph clustering or community detection is normally used to comprehend the structure of complex networks and to retrieve meaningful information from...
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Scholarly Community
This chapter provides an overview of the scholarly communities in which the digital 3D reconstruction is used as a method. (Visual) digital...
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TSInc: Tie strength based incremental community detection using information cascades
Community detection in dynamic networks is of great importance in social network analysis. For instance, online social networks such as Facebook,...
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Fast local community discovery relying on the strength of links
Community detection methods aim to find nodes connected to each other more than other nodes in a graph. As they explore the entire network, global...
