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Physical Sciences and Mathematics

Technological University Dublin

2017

Deep learning

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Back To The Future: Logic And Machine Learning, Simon Dobnik, John D. Kelleher Jun 2017

Back To The Future: Logic And Machine Learning, Simon Dobnik, John D. Kelleher

Conference papers

In this paper we argue that since the beginning of the natural language processing or computational linguistics there has been a strong connection between logic and machine learning. First of all, there is something logical about language or linguistic about logic. Secondly, we argue that rather than distinguishing between logic and machine learning, a more useful distinction is between top-down approaches and data-driven approaches. Examining some recent approaches in deep learning we argue that they incorporate both properties and this is the reason for their very successful adoption to solve several problems within language technology.


Tackling The Interleaving Problem In Activity Discovery, Eoin Rogers, Robert J. Ross, John D. Kelleher Jun 2017

Tackling The Interleaving Problem In Activity Discovery, Eoin Rogers, Robert J. Ross, John D. Kelleher

Conference papers

Activity discovery (AD) is the unsupervised process of discovering activities in data produced from streaming sensor networks that are recording the actions of human subjects. One major challenge for AD systems is interleaving, the tendency for people to carry out multiple activities at a time a parallel. Following on from our previous work, we continue to investigate AD in interleaved datasets, with a view towards progressing the state-of-the-art for AD.


Review Of Trends In Health Social Media Analysis, Liliya Akhtyamova, Mikhail Alexandrov, John Cardiff Jan 2017

Review Of Trends In Health Social Media Analysis, Liliya Akhtyamova, Mikhail Alexandrov, John Cardiff

Conference Papers

This paper surveys recent publications (2008-2017) on using social media data to study public health. The survey describes the main topics being discussed in forums and presents short information about methods and tools used for analysis health social media. We put especial attention on adverse drug reaction detection problem (ADR).