dot.kom project full details
Champion:
John Domingue
Professor of Computer Science
Participant(s):Enrico Motta, Victoria Uren, Barry Norton, Jianhan Zhu
Timeline:01 Oct 2002 - 31 Mar 2005
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DOT.KOM
Designing adaptive infOrmation exTraction from text for KnOwledge Management
DotKom aims to support knowledge management within large corporation through a combination of information extraction and knowledge management technologies. A current problem with both of these technologies is that they are hard-to-use and require extensive expertise. DotKom will provide user-friendly *adaptive* information extraction tools which give instantaneous feedback on the current status of the information extraction learning process and the automatically constructed knowledge acquisition mechanisms.
News
09 Oct 2002
KMi News
Siddharthan, A., Ponnamperuma, K., Mellish, C., Zeng, C., Heptinstall, D., Robinson, A., Benn, S. and van der Wal, R. (2019). Blogging Birds: Telling informative stories about the lives of birds from telemetric data. Communications of the ACM, 62(3), pp. 68–77. https://oro.open.ac.uk/55341/.
van der Wal, R., Sharma, N., Mellish, C., Robinson, A. and Siddharthan, A. (2016). The role of automated feedback in training and retaining biological recorders for citizen science. Conservation Biology, 30(3), pp. 550–561. https://oro.open.ac.uk/51049/.
Siddharthan, A., Lambin, C., Robinson, A.M., Sharma, N., Comont, R., O’Mahony, E., Mellish, C. and Van Der Wal, R. (2016). Crowdsourcing Without a Crowd: Reliable Online Species Identification Using Bayesian Models to Minimize Crowd Size. ACM Transactions on Intelligent Systems and Technology, 7(4), https://oro.open.ac.uk/51046/.
