Titlebook: Big Data Analytics and Knowledge Discovery; 20th International C Carlos Ordonez,Ladjel Bellatreche Conference proceedings 2018 Springer Nat

Antioxidant

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

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

SMART

厭食癥

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

Antigen

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

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

令人發(fā)膩

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

使激動

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.