Clustering is a well-known unsupervised machine learning approach capable of
automatically grouping discrete sets of instances with similar characteristics. Constrained …

Extracting valuable insights from a large volume of unstructured data such as texts through
clustering analysis is paramount to many big data applications. However, document …

In this work, we aim to discover real-world events from Flickr data by devising a three-stage
event detection framework. In the first stage, a multimodal fusion (MF) model is designed to …

Clustering is an important technique in organising and categorising web scale documents.
The main challenges faced in clustering the billions of documents available on the web are …

The problem of clustering a large document collection is not only challenged by the number
of documents and the number of dimensions, but it is also affected by the number and sizes …

Document clustering is one of the prominent methods for mining important information from
the vast amount of data available on the web. However, document clustering generally …

This paper outlines the approach taken by the Speech, Audio, Image and Video
Technologies laboratory, and the Applied Data Mining Research Group (SAIVT-ADMRG) in …

Multimodal image clustering becomes an effective approach for social event detection in
large photo collections. In addition to visual and textual information, geographic information …

To gain insight on a large amount of text data collected by social media outlets is
challenging, even availed with the latest advancement of big data technology. In addition to …

В статье рассматривается медийное представление инвестиционных форумов РФ как
показатель внешнего внимания к мероприятию и его узнаваемости для сравнительного …