Social networks have been regarded as a timely and cost-effective source of spatio-temporal
information for many fields of application. However, while some research groups have …

Social media becomes a vital part in our daily communication practice, creating a huge
amount of data and covering different real-world situations. Currently, there is a tendency in …

Document clustering has been recognized as a central problem in text data management.
Such a problem becomes particularly challenging when document contents are …

Clustering algorithms are used to assess the interaction among documents by organizing
documents into clusters such that document within a cluster are more similar to each other …

Document clustering techniques have been applied in several areas, with the web as one of
the most recent and influential. Both general-purpose and text-oriented techniques exist and …

Text classification is becoming a crucial task to analysts in different areas. In the last few
decades, the production of textual documents in digital form has increased exponentially …

Clustering is a useful technique to create different groups of objects on the basis of their
nature. Objects of same group are of similar in nature and differ to the objects of other …

Topics that attract public attention can originate from current events or developments, might
be influenced by situations in the past, and often continue to be of interest in the future …

The dilemma between stability and plasticity is crucial in machine learning, especially when
non-stationary input distributions are considered. This issue can be addressed by continual …

In this paper, we evaluate the effectiveness of a semantic smoothing technique to organize
folksonomy tags. Folksonomy tags have no explicit relations and vary because they form …