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Professor Yannis Korkontzelos

Professor of Computing

Department of Computer Science

Department: Department of Computer Science

ORCID logo https://orcid.org/0000-0001-8052-2471 View full profile

Profile

Biography

Yannis is a Reader in Computer Science, with a research focus on a variety of subfields of Natural Language Processing and Text Mining, such as compositional semantics, multiword expression and term extraction, document classification and sentiment analysis, applied to a number of domains, such as biomedicine, social sciences, social media, open source software and scientific publications.

Yannis holds a PhD in Computer Science from the University of York, an MPhil in Computer Text, Speech and Internet Technology from the University of Cambridge and a first class honours Diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece.

Prior to joining the Department of Computer Science, Edge Hill University, he was employed as a Research Fellow at the National Centre for Text Mining (NaCTeM), University of Manchester. Among other projects, he was involved in the development, write up and successful completion of OSSMETER, an EU FP7 STReP project that developed an innovative platform for automatically analysing and measuring open-source software to support decision makers in the process of discovering, comparing, assessing and monitoring the health, quality, impact and activity of open-source software. He was also involved in ISHER (Integrated Social History Environment for Research – Digging into Social Unrest), one of the 14 projects that won the second Digging Into Data Challenge (JISC) in 2011. The project resulted in an integrated environment that indexes all articles published in the New York times in 20 years. The environment can be used as a novel exploratory tool for scientists to answer research questions quickly and accurately.

Research Interests

Natural Language Processing, Text Mining, Social media analysis, Machine Learning

Teaching

  • Big Data
  • Applications in Big Data