Topic modelling is the new revolution in text mining. It is a statistical technique for revealing
the underlying semantic structure in large collection of documents. After analysing …

Topic modeling is one of the most powerful techniques in text mining for data mining, latent
data discovery, and finding relationships among data and text documents. Researchers …

Exploiting machine learning techniques for analyzing programs has attracted much
attention. One key problem is how to represent code fragments well for follow-up analysis …

As a particular subfield of futures studies, foresight evaluation has not yet been thoroughly
studied. This paper investigates research on foresight evaluation, reviewing authors …

With the growth of online social network platforms and applications, large amounts of textual
user-generated content are created daily in the form of comments, reviews, and short-text …

Defect prediction models-classifiers that identify defect-prone software modules-have
configurable parameters that control their characteristics (eg, the number of trees in a …

Deep learning subsumes algorithms that automatically learn compositional representations.
The ability of these models to generalize well has ushered in tremendous advances in many …

The popularity of mobile devices has been steadily growing in recent years. These devices
heavily depend on software from the underlying operating systems to the applications they …

Context Topic modeling finds human-readable structures in unstructured textual data. A
widely used topic modeling technique is Latent Dirichlet allocation. When running on …

Software traceability is a sought-after, yet often elusive quality in software-intensive systems.
Required in safety-critical systems by many certifying bodies, such as the USA Federal …