Many automated software engineering approaches, including code search, bug report
categorization, and duplicate bug report detection, measure similarities between two …

Mobile healthcare is an emerging technique for clinical applications. It is usually based on
cloud-connected biomedical implants. In this context, a novel solution is presented for the …

Fixing software bugs and adding new features are two of the major maintenance tasks.
Software bugs and features are reported as change requests. Developers consult these …

Topic modeling methods proved to be effective for inferring latent topics from short texts.
Dealing with short texts is challenging yet helpful for many real-world applications, due to …

Feature selection is critical in reducing the size of data and improving classifier accuracy by
selecting an optimum subset of the overall features. Traditionally, each feature is given a …

Co-clustering refers to the simultaneous clustering of objects and their features. It is used as
a clustering technique when the data exhibit similarities only in a subset of features instead …

Measuring the similarity of words is important in accurately representing and comparing
documents, and thus improves the results of many natural language processing (NLP) tasks …

The success of machine learning approaches to word sense disambiguation (WSD) is
largely dependent on the representation of the context in which an ambiguous word occurs …

Multi-view clustering has gained importance in recent times due to the large-scale
generation of data, often from multiple sources. Multi-view clustering refers to clustering a set …

In many clustering problems, we have access to multiple sources of data representing
different aspects of the problem. Each of these data separately represents an association …