Logic and Computation (Introductory)
Second week, from 9:00 to 10:30
Argumentation mining aims at automatically extracting arguments from textual corpora, to provide structured data for computational models of argument and reasoning engines. It has recently become a hot topic also due to its potential in processing information from the Web (social media, online newspapers, product reviews, etc.). In a typical argumentation mining pipeline, sentences recognized as argumentative are extracted from the input document, and argument components (claims and supporting evidences) are identified within such sentences. Then, links between argument components are predicted to construct complete arguments. Finally, the connections between arguments are inferred (
e.g., support and attack relations), so as to produce a complete argument graph. Recent advances in computational linguistics and machine learning promise to enable breakthrough applications to this research area. In this course, we introduce argumentation models and methods, review existing systems and applications, and discuss challenges and perspectives of this new research area.