<div>Wow, what a fantastic response.</div><div><br></div><div>I've got plenty of homework here now, and plenty of people to speak to individually about this.</div><div><br></div><div>Thanks LRUG!</div><div><br></div><div>C</div><div><div><br></div><div><br></div><div>-- </div><div>Chris Adams</div><div>mobile: 07974 368 229</div><div>twitter: @mrchrisadams</div><div>www: chrisadams.me.uk</div><div><br></div></div>
<p style="color: #A0A0A8;">On Monday, 20 August 2012 at 15:49, Chris Lowis wrote:</p>
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<span><div><div><blockquote type="cite"><blockquote type="cite"><div><div>I'm trying to spec out a feature at work, to sift through a load of text in</div><div>case studies or similar articles, and categorise them according to some</div><div>pre-determined criteria, and present them later to users of an app we're</div><div>build, to help them discover useful steps their business on take to reduce</div><div>emissions.</div></div></blockquote></blockquote><div><br></div><div>We've (BBC R&D) been doing something similar to this and have had</div><div>quite a bit of success using Wikipedia Miner[1], and have also</div><div>implemented our own term extraction code to work with noisy</div><div>speech-to-text transcripts. Happy to talk more about what we've been</div><div>doing with you if it looks like something that might help.</div><div><br></div><div>Cheers,</div><div><br></div><div>Chris</div><div><br></div><div>[1] <a href="http://wikipedia-miner.cms.waikato.ac.nz">http://wikipedia-miner.cms.waikato.ac.nz</a>/</div><div>_______________________________________________</div><div>Chat mailing list</div><div><a href="mailto:Chat@lists.lrug.org">Chat@lists.lrug.org</a></div><div><a href="http://lists.lrug.org/listinfo.cgi/chat-lrug.org">http://lists.lrug.org/listinfo.cgi/chat-lrug.org</a></div></div></div></span>
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