• graph2vec

  • Referenced in 10 articles [sw32340]
  • structured data predominantly focus on learning distributed representations of graph substructures such as nodes ... analytics tasks such as graph classification and clustering require representing entire graphs as fixed length ... such as graph classification, clustering and even seeding supervised representation learning approaches. Our experiments ... significant improvements in classification and clustering accuracies over substructure representation learning approaches and are competitive...
  • GraRep

  • Referenced in 21 articles [sw32342]
  • such as clustering, classification and visualization. Empirical results demonstrate that our representation significantly outperforms other...
  • Indclus

  • Referenced in 23 articles [sw20757]
  • discrete) clustering counterpart to the Carroll-Chang INDSCAL model for (continuous) spatial representations. Finally...
  • MAPCLUS

  • Referenced in 31 articles [sw20021]
  • discrete (0,1) constraints on parameters defining cluster membership. This procedure is supplemented by several ... purpose computer implemented algorithm for obtaining ADCLUS representations. MAPCLUS is illustrated with an application ... MAPCLUS solution uses half as many clusters to achieve nearly the same level of goodness...
  • clus

  • Referenced in 8 articles [sw26389]
  • improve these graphical representations considerably. The integration of the clustering algorithms was performed according...
  • Higra

  • Referenced in 2 articles [sw32589]
  • Higra are the construction of hierarchical representations (agglomerative clustering, mathematical morphology hierarchies, etc.), the analysis ... processing of such representations (filtering, clustering, characterization, etc.), and their assessment. Higra targets a large...
  • Xproj

  • Referenced in 6 articles [sw12722]
  • structural clustering of xml documents. XML has become a popular method of data representation both ... problems. One such problem is that of clustering, in which the structural aspects ... data representation. As a result, it becomes more difficult to cluster the data...
  • GeneRAGE

  • Referenced in 5 articles [sw35909]
  • accurate family representation for each protein in the dataset. Initial clusters containing multi-domain families...
  • SAINTETIQ

  • Referenced in 17 articles [sw02290]
  • named SAINTETIQ. Based on a hierarchical conceptual clustering algorithm, SAINTETIQ incrementally builds a summary hierarchy ... database records. Furthermore, the fuzzy set-based representation of data allows to handle vague, uncertain...
  • ProTraS

  • Referenced in 2 articles [sw33763]
  • results in terms of quality of representation for clustering, sampling size and sampling time...
  • fabMix

  • Referenced in 4 articles [sw32111]
  • /j.csda.2018.03.007>). The number of clusters is estimated using overfitting mixture models (Rousseau and Mengersen ... give rise to parsimonious representations of the covariance per cluster (following Mc Nicholas and Murphy...
  • FisherEM

  • Referenced in 2 articles [sw40281]
  • high-dimensional data. FisherEM models and clusters the data in a discriminative and low-dimensional ... also provides a low-dimensional representation of the clustered data. A sparse version of Fisher...
  • ClusterSignificance

  • Referenced in 1 article [sw35614]
  • assess if class clusters in dimensionality reduced data representations have a separation different from permuted ... assess if class clusters in dimensionality reduced data representations have a separation different from permuted...
  • BoostCluster

  • Referenced in 5 articles [sw08555]
  • clustering algorithm with the side information since clustering algorithms by definition are unsupervised. The proposed ... representations at each iteration that are, on the one hand, adapted to the clustering results...
  • VeRNAl

  • Referenced in 1 article [sw39988]
  • finding problem as a graph representation learning and clustering task. This framing takes advantage ... continuous nature of graph representations to model the flexibility and variability of RNA motifs ... propose a set of node similarity functions, clustering methods, and motif construction algorithms to recover...
  • subgraph2vec

  • Referenced in 4 articles [sw36496]
  • Deep Learning and Graph Kernels. These latent representations encode semantic substructure dependencies in a continuous ... models for tasks such as graph classification, clustering, link prediction and community detection. subgraph2vec leverages ... neighbourhoods of nodes to learn their latent representations in an unsupervised fashion. We demonstrate that ... such as CNNs, SVMs and relational data clustering algorithms to achieve significantly superior accuracies. Also...
  • FaceNet

  • Referenced in 30 articles [sw21626]
  • tasks such as face recognition, verification and clustering can be easily implemented using standard techniques ... benefit of our approach is much greater representational efficiency: we achieve state...
  • MDMC2

  • Referenced in 1 article [sw17668]
  • Monte Carlo simulations of multiply charged clusters in the NVTNVT ensemble (Bonhommeau and Gaigeot ... mesoscopic coarse-grained simplified representation of the clusters (or droplets): these clusters are composed...
  • PhyloNet

  • Referenced in 11 articles [sw20725]
  • classified into four categories: (1) evolutionary network representation: reading/writing evolutionary networks in a newly devised ... terms of three basic building blocks - trees, clusters, and tripartitions; (3) evolutionary network comparison: comparing ... supports the proposed eNewick format for compact representation of evolutionary networks, a feature that allows...
  • metapath2vec

  • Referenced in 11 articles [sw37749]
  • network embedding techniques. We develop two scalable representation learning models, namely metapath2vec and metapath2vec ... network mining tasks, such as node classification, clustering, and similarity search, but also discern...