Research Seminar

Video content relating to a Research Seminar in the School of Computing

Dr. Volker Sorge - Seminar Talk - 14th June 2016

Video Category: 
Research Seminar Talk
Dr. Volker Sorge

Title: Making STEM Content Accessible in the Age of the Web

Sponsored by the ADAPT Centre and the Faculty of Engineering &
Computing Enhancing Performance Fund.

Prof Nabor Mendonça - Seminar Talk - 23rd February 2015

Video Category: 
Research Seminar Talk
Prof Nabor Mendonça

Title: Cloud Detours: A Non-Intrusive Approach for Automatically Adapting Legacy Applications to the Cloud

Seminar: Joint IC4/Lero Research Seminar

Ahmed Ragheb - Seminar Talk - 20th November 2013

Video Category: 
Research Seminar Talk

Title: UIMA - The Open Architecture That Helps Watson Understand Human Language

Dr. Hang Li - Seminar Talk - 1st August 2013

Video Category: 
Research Seminar Talk
Dr. Hang Li


The Future of Natural Language Processing


In this talk, I will give a review on the current state of natural language processing (NLP), including information retrieval, and discuss the future trends in the field. Past years have observed significant advancement of natural language processing technologies; web search, machine translation, and other NLP products have become an integral part of our everyday life; Apple Siri and IBM Watson have demonstrated the great potential of NLP, and made big impact in the society; the performances on the basic tasks including lexical analysis, syntactic analysis, and semantic analysis have been made significantly enhanced. On the other hand, there is still a long way to go, before we achieve the ultimate goal of letting computers to understand human language, naturally communicate with humans, and help humans to accomplish tasks.  NLP is also facing new opportunities and challenges, in the era of cloud computing, big data, and social computing.  I predict that semantic matching, large scale machine learning, and human defined knowledge will be important keywords for NLP in the coming decade, and argue that intensive investigations should be made on the related technologies and breakthroughs could be made. I will introduce some of our related works and take them as examples to describe semantic matching, large scale machine learning, and human defined knowledge.

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