Professor Ruslan Mitkov is an expert in Computational
Linguistics at the University of Wolverhampton. He is Director of
the Research Institute for Information and Language Processing and
Head of the Research Group in Computational
Research in this area recently scored highly in the Research
Assessment Exercise (RAE 2008). The research of the group has been
rated as internationally leading, internationally excellent and
internationally recognised. According to league tables published in
the Guardian, The Times and Research Fortnight, research in
Linguistics at the University of Wolverhampton is one of the top
six in the UK.
Computational Linguistics has to do with the processing of human
languages by computers. This could involve understanding or
translating. For example, imagine you have to find the answer to
the question ‘When were potatoes first imported into Britain?’ If
you do a keyword search, the search engine will return 100s of
matches containing the words ‘potatoes’ and ‘Britain’ but will not
give you the answer. But one of the technologies we developed,
called Question Answering, understands your question and finds and
provides the answer for you. It is worth pointing out that
computers find it very difficult to understand human languages due
to the ambiguity and irregularity of language – so if I said, “I
saw John with binoculars” it would not understand if I had used the
binoculars to see John, or I had seen John using the binoculars. Of
course, ambiguity is a problem for humans too but it is much harder
One of the applications we have developed is called automatic
summarisation. This is a program that can read a lot of pages in a
second and generate a summary of the most important text for you.
Another application is a program we are working on with the
National Board of Medical Examiners (USA) where the system reads
medical texts and generates multiple choice tests.
I enjoy the fact that Computational Linguistics, often referred
to as Natural Language Processing when talking about applied
research, could be used in many areas of life. Our priorities at
the moment are to use our technology in healthcare and e-learning.
An example of what we would like to develop is a tool that will
assist people with dyslexia or dementia and make it easier for them
to read complicated texts.
I am working on 20-plus topics at the moment! My favourite
topics currently are the automatic generation of multiple choice
tests and the use of Natural Language Processing in teaching
foreign languages. In addition, we are developing tools that will
improve the efficiency of translators. I am also well known for my
work on anaphora resolution – this is the challenging task of the
computer being able to identify references (eg. whom or what
pronouns refer to) in text. I generate a lot of ideas and many of
them I pass on to our PhD students and we work on them
I am engaging in more and more international collaborations,
with a view to securing more external funding for research. I am
looking forward to commercialising some of our products and the
possibility of setting up a start-up company. I would not feel
satisfied if my research was not beneficial to society, so my dream
is to use our technology to improve medical care as a legacy to my
late parents, who were both medical doctors and I owe them a lot in
terms of my academic career.
Natural Language Processing cannot wave a wand and solve all the
problems, but we would want to advance this area in the next five
years. Little advances can make a real difference in this field,
and the applied research we are involved in can be of practical use
to many areas of society.
I think seeing people in my field cite my work and read my
books. Another personal achievement is when I am invited to
conferences and meet young researchers who have said they have
wanted to meet me and that my work had helped them to develop their
own research successes.
Hopefully the RAE results will motivate us even further, and
help us to attract more funding for research and more top
researchers. I am very pleased that the RAE success was not an
individual but a collective success within the Research Group in
Computational Linguistics and the Research Institute for
Information and Language Processing.
I think the most unusual thing is that to be a success in this
field you need to have a background in computer science,
mathematics and linguistics. We collaborate with people from all
kinds of backgrounds. The difficulty of computers understanding
human language due to its ambiguity, irregularity and in general,
complexity, is a major challenge.
Some people think that we are trying to replace humans but we
are not – we are trying to develop programs which help humans.
People also think that computers can do wonders, but they cannot.
They are not as intelligent as humans and they should not be.
Natural Language Processing should be used in specific scenarios
and in specific domains. It is only then that it can be
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