Big data is often characterized by a huge volume and a mixed types of attributes namely,
numeric and categorical. K-prototypes has been fitted into MapReduce framework and …

Textual data frequently occurs as an unlabeled document collection, therefore it is useful to
sort this collection into clusters of related documents. On the other hand, text has different …

Big Data clustering has become an important challenge in data analysis since several
applications require scalable clustering methods to organize such data into groups of similar …

Clustering textual data has become an important task in data analytics since several
applications require to automatically organizing large amounts of textual documents into …

Nowadays, trends detection is an important task on social media to determine trends that are
being discussed the most on a social platform. One of the main challenges of this task is the …

Clustering is one of the most important unsupervised machine learning tasks. It is widely
used to solve problems of intrusion detection, text analysis, image segmentation etc …

The rapid development of different techniques and the data are accumulated with distinctive
properties with high dimensions and huge size. The most essential approach in data mining …

Big data is often characterized by a huge volume and a mixed types of attributes namely,
numeric and categorical. K-prototypes is one of the most well-known clustering methods to …

Big data is often characterized by a huge volume and mixed types of data including numeric
and categorical. The k-prototypes is one of the best-known clustering methods for mixed …

We analyse the application of various interfaces to facilitate exploratory search and
summarization of documents, especially BubbleNet, an innovative interface for summarizing …