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Numerous different clustering algorithms have been proposed, striving to circumvent the high mobility of vehicles which negatively affect the communication abilities.

This metric is called the modularity, or Q function (Newman and Girvan, 2004), and numerous graph clustering algorithms have been developed to identify clusters that optimize modularity (Blondel et al., 2008; Clauset et al., 2004; Newman and Girvan, 2004; Wakita and Tsurumi, 2007).

A range of chemical descriptors and structural features can be computed by CheS-Mapper and numerous clustering and embedding algorithms are available.

Considering that numerous pattern recognition and clustering algorithms exist it is likely that the resulting clustering will be different in each case, although some degree of consensus might be expected.

Many clustering algorithms like KMCA, HCA are hard clustering algorithms.

Hierarchical clustering algorithms produce a hierarchy of nested clustering.

Reported clustering algorithms are designed to form natural clusters.

"Our proprietary clustering algorithms automatically cluster our customer's historical data (chat, email, knowledge base) to train our neural network.

This chapter discusses the hierarchical clustering algorithms.

DBSCAN algorithm is one of the density-based clustering algorithms.

Both clustering ensemble and semi-supervised clustering techniques have been emerged to improve the clustering performance of unsupervised clustering algorithms.

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