Transcript for Keynote Presentation: Implementing large scale Machine Translation in Patent Information

Good morning ladies and gentlemen

I would like first of all thank the organizers for giving me the opportunity to speak here

The honor to be able to kick off the conference with the keynote

As you can see I am going to be talking about the implementation of machine translation in a relatively large scale environment

And am going to look at it from an end-users perspective

So while I know the conference is going to talk about a lot of technical details on

machine translation and localization. This presentation is very much from an end users perspective.

From a large end-users perspective

With me today also is one of my team members

who also happens to be, by the way, the MT expert in my team

So if you have any specific questions later on

in the break, I would be very happy to introduce you and you will get all the details that you would like

With that let me go through and have a quick look at the agenda with you

So what I would like to talk about first of all is just give you a very quick introduction on who we are

no marketing slides don't worry

just to give you a bit of an appreciation of where we fit

and then go onto to talk about the challenges related to MT

from our perspective, how we had been dealing with MT in the past.

And how we are evolving our systems.

And a few comments on the remaining challenges that remain.

To give you a bit of an idea on who we are

Lexis Nexis is a name that you might not have heard before,

we are part of the Reed Elsevier group,

which is pretty large in scientific, medical, technical data

content providers, about 20,000 employees, 400 companies globally.

And Lexis Nexis is a strong player in business content, legal and patent information.

The organization I look after is very small.

We are a small part of the organization, but in the patent world we are a prime supplier of information.