Fake news has become more prevalent than ever, correlating with the rise of social media
that allows every user to rapidly publish their views or hearsay. Today, fake news spans …

During a research project in which we developed a machine learning (ML) driven
visualization system for non-ML experts, we reflected on interpretability research in ML …

Research in emotion analysis of text suggest that emotion lexicon based features are
superior to corpus based n-gram features. However the static nature of the general purpose …

With the growing variety of entities that have their presence on the web, retrieving relevant
entities for various user requirements becomes an important problem. The area of Similarity …

Multiple instance learning is a challenging task in supervised learning and data mining.
However, algorithm performance becomes slow when learning from large-scale and high …

Abstract Community-driven Question Answering (CQA) systems that crowdsource
experiential information in the form of questions and answers and have accumulated …

Currently, many intelligence systems contain the texts from multi-sources, eg, bulletin board
system posts, tweets and news. These texts can be “comparative” since they may be …

We propose an architecture for the design of representative-based clustering algorithms
based on reusable components. These components were derived from K-means-like …

The problem of detecting spatially-coherent groups of data that exhibit anomalous behavior
has started to attract attention due to applications across areas such as epidemic analysis …

The analysis of microarray data is fundamental to microbiology. Although clustering has long
been realized as central to the discovery of gene functions and disease diagnostic …