Improving disaster management and recovery techniques is one of national priorities given
the huge toll caused by man-made and nature calamities. Data-driven disaster management …

In recent years, social networking sites have not only enabled people to connect with each
other using social links but have also allowed them to share, communicate and interact over …

In this paper, we discuss how we can extend probabilistic topic models to analyze the
relationship graph of popular social-network data, so that we can group or label the edges …

The evolution of the Web has promoted a growing interest in social network analysis, such
as community detection. Among many different community detection approaches, there are …

Social annotation has gained increasing popularity in many Web-based applications,
leading to an emerging research area in text analysis and information retrieval. This paper is …

Social (or folksonomic) tagging has become a very popular way to describe, categorise,
search, discover and navigate content within Web 2.0 websites. Unlike taxonomies, which …

One of the main organizing principles in real-world networks is that of network communities,
where sets of nodes organize into densely linked clusters. Even though detection of such …

With social interaction playing an increasingly important role in the online world, the
capability to extract latent communities based on such interactions is becoming vital for a …

Early search engines retrieved relevant pages for the user based primarily on the content
similarity of the user query and the indexed pages of the search engines. The retrieval and …

Topic modeling techniques have widespread use in text data mining applications. Some
applications use batch models, which perform clustering on the document collection in …