In many modern data management scenarios, we encounter tasks, operations or computational phases that are data-intensive where the sheer volume of data proves to be overwhelming to handle and becomes a performance bottleneck. ...

Text simplification is a task in the natural language processing field that alters a given text to reduce the structural and lexical complexity of the text while preserving the underlying meaning. We can classify existing ...

We present a new iterative approach towards unsupervised edit-based sentence simplification. Our approach is guided by a scoring function to select simplified sentences generated after iteratively performing word and ...

While Convolutional Neural Networks (CNN) achieve state-of-the-art predictive performance in applications such as computer vision, their predictions are difficult to explain, similar to other types of deep learning models. ...

Ordered domains such as numbers and dates are common in real-life datasets. The SQL standard includes an ORDER BY clause to sort the results, and there has been research work on formalizing, reasoning about, and automatically ...

Addressing gender issues has become important worldwide. The United Nations (UN) endorses big data projects as a valuable tool to monitor its gender-related development goals. In this thesis, we first motivate the examination ...