Data clustering is a commonly used data processing technique in many fields, which divides
objects into different clusters in terms of some similarity measure between data points …

Web clustering engines organize search results by topic, thus offering a complementary
view to the flat-ranked list returned by conventional search engines. In this survey, we …

Clustering is a widely studied data mining problem in the text domains. The problem finds
numerous applications in customer segmentation, classification, collaborative filtering …

As recently as the 1990s, studies showed that most people preferred getting information
from other people rather than from information retrieval systems. Of course, in that time …

The existing deep multiview clustering (MVC) methods are mainly based on autoencoder
networks, which seek common latent variables to reconstruct the original input of each view …

Mobile application markets such as the Android Marketplace provide a centralized
showcase of applications that end users can purchase or download for free onto their mobile …

Modern cloud systems have a vast number of components that continuously undergo
updates. Deploying these frequent updates quickly without breaking the system is …

Clustering is a fundamental technique in data mining and pattern recognition, which has
been successfully applied in several contexts. However, most of the clustering algorithms …

Community detection (or graph clustering) is crucial for unraveling the structural properties
of complex networks. As an important technique in community detection, label propagation …

Semantic Web documents that encode facts about entities on the Web have been growing
rapidly in size and evolving over time. Creating summaries on lengthy Semantic Web …