Antioxidant
发表于 2025-3-28 14:55:01
Community Detection in Who-calls-Whom Social Networksocus on the community detection problem which is extremely challenging and it has many practical applications. We have used Apache Spark with the . community detection algorithm using a cluster of machines, to study the scalability and efficiency of the proposed methodology. The experimental evaluation is based on real-world mobile phone data.
Critical
发表于 2025-3-28 20:39:00
KMN - Removing Noise from K-Means Clustering Results the number of clusters. Moreover, it is completely parameter-free. The technique has been tested on artificial and real data sets to demonstrate its performance in comparison with other noise-excluding techniques for k-means.
磨坊
发表于 2025-3-29 02:06:46
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SMART
发表于 2025-3-29 07:07:30
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厌食症
发表于 2025-3-29 08:33:19
Effective Classification of Ground Transportation Modes for Urban Data Mining in Smart Citiesorks, our system increases the classification accuracy by uniquely using GPS and accelerometer data together with a window history queue (which uses previously encountered data). Evaluation results show that our system achieves a high classification accuracy.
帽子
发表于 2025-3-29 14:36:45
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Antigen
发表于 2025-3-29 16:34:13
An Efficient Prototype Selection Algorithm Based on Spatial Abstractionte-of-the-art algorithms, considering two measures: accuracy and reduction. All the obtained results show that, in general, the proposed approach provides a good trade-off between accuracy and reduction, with a significantly lower running time, when compared to other approaches.
tariff
发表于 2025-3-29 21:19:33
Wide-Line NMR and Protein Hydrationa is to partially delegate computational load to a set of federated RDF triple stores in a peer-to-peer manner thus reducing the computational burden on a centralised query processing server. In our preliminary investigation, we evaluate FedS against the state-of-the-art approaches that provide the
令人发腻
发表于 2025-3-30 02:30:16
Matthew D. Smith,Masoud Jelokhani-Niarakith high traffic, this paper proposes and evaluates a graph theory based approach for calculating road priorities purely based on the topological structure of the road network. The work further demonstrates the utility of the . sub-network in terms of both, achieving gains in path computation and cap
使激动
发表于 2025-3-30 05:40:18
Vladimir N. Uversky,A. Keith Dunkerorks, our system increases the classification accuracy by uniquely using GPS and accelerometer data together with a window history queue (which uses previously encountered data). Evaluation results show that our system achieves a high classification accuracy.