Data fusion is the process of merging records from multiple sources which represent the
same real-world object into a single representation. This review of the literature concerns …

Truth discovery methods aim to identify which piece of information is trustworthy from multi-
sourced data. Most existing truth discovery methods, however, are designed for structured …

Understanding the results of deep neural networks is an essential step towards wider
acceptance of deep learning algorithms. Many approaches address the issue of interpreting …

In the era of big data, fragmented knowledge, multisource heterogeneity, and different
representation forms of the same entities in various data sources have posed considerable …

Many approaches exist for analysing fact checking for fake news identification, which is the
focus of this thesis. Current approaches still perform badly on a large scale due to a lack of …

In the era of information explosion, plenty of data has been generated through a variety of
channels, such as social networks, crowdsourcing platforms and blogs. Conflicts and errors …

Latent truth discovery, LTD for short, refers to the problem of aggregating ltiple claims from
various sources in order to estimate the plausibility of atements about entities. In the …

As more people rely on online media, it becomes more challenging to identify trustworthy
information. As a result of this increased complexity, stance detection and rumour detection …