UCREL/Data Science Group Seminar

Thursday 31 May 2018, 3:00pm to 4:00pm

Venue

Infolab D55 - View Map

Open to

Postgraduates, Staff

Registration

Registration not required - just turn up

Event Details

Effective Semantics for Engineering NLP Systems

Abstract:At the center of many Natural Language Processing (NLP) applications is the requirement for capturing and interpreting commonsense and domain-specific knowledge at scale. The selection of the right semantic and knowledge representation model plays a strategic role for building NLP systems ( e.g. Question Answering, Sentiment Analysis, Semantic Search) which effectively work with real data. In this talk, we will provide an overview of emerging trends in semantic representation for building NLP systems which can cope with large-scale and heterogeneous textual data. Based on empirical evidence, we will provide a description of the strengths and weaknesses of different representation perspectives, aiming towards a synthesis: ‘a semantic model to rule them all’.

Speaker

André Freitas

University of Manchester

André Freitas is a lecturer at the School of Computer Science at the University of Manchester. Prior to Manchester, he was an associate researcher and lecturer at the Natural Language Processing and Semantic Computing Group at the University of Passau (Germany). His main research areas include Question Answering, Hybrid Symbolic-Distributional Models and Natural Language Inference.

Contact Details

Name Andrew Moore
Email

a.moore@lancaster.ac.uk

Website

http://ucrel.lancs.ac.uk/crs/presentation.php?id=181