no code implementations • CL 2019 • John Lawrence, Chris Reed
Argument mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language.
no code implementations • WS 2019 • John Lawrence, Jacky Visser, Chris Reed
Understanding the inferential principles underpinning an argument is essential to the proper interpretation and evaluation of persuasive discourse.
no code implementations • WS 2017 • John Lawrence, Chris Reed
In this paper we consider the insights that can be gained by considering large scale argument networks and the complex interactions between their constituent propositions.
no code implementations • WS 2017 • John Lawrence, Chris Reed
These statements are then used to produce a matrix representing the inferential relationship between different aspects of the topic.
no code implementations • 3 Feb 2017 • Jaimie Murdock, Colin Allen, Katy Börner, Robert Light, Simon McAlister, Andrew Ravenscroft, Robert Rose, Doori Rose, Jun Otsuka, David Bourget, John Lawrence, Chris Reed
We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for interdisciplinary research.
no code implementations • LREC 2016 • Barbara Konat, John Lawrence, Joonsuk Park, Katarzyna Budzynska, Chris Reed
Governments are increasingly utilising online platforms in order to engage with, and ascertain the opinions of, their citizens.