The problem of clustering is perhaps one of the most widely studied in the data mining and
machine learning communities. This problem has been studied by researchers from several …

The explosive growth of user-generated contents in social networking websites necessitates
the recommendation functionality that can push to the user the content that he/she is most …

Nous proposons une méthode de soft subspace clustering basée sur les cartes
topologiques pour la classification d'individus décrits par des variables structurées en blocs …

High-dimensional indexes do not work because of the often-cited “curse of dimensionality.”
However, users are usually interested in querying data over a relatively small subset of the …

In this paper presents an enhanced k-means type algorithm for clustering high-dimensional
objects. In high dimensional data, clusters of objects often exist in subspaces rather than in …

A need has long been identified for a more effective methodology to understand, prevent,
and cure cancer. Microarray technology provides a basis of achieving this goal, with cluster …

In recent years, M2M (Machine-to-Machine) applications have become more diverse and
widespread because of a reduction in price and growth in the capacity of network …

我々はスキーマレス検索と呼ばれる新しい検索の効率を向上させるインデキシング手法, UBI-Tree
を提案する. スキーマレス検索は参加型センシングを用いて収集したセンサデータなどの …