KMi Seminars
Integrating Human & Machine Document Annotation for Sensemaking
This event took place on Thursday 11 November 2010 at 14:30

 
Dr Simon Buckingham Shum

Simon Buckingham Shum, Ágnes Sándor, Anna De Liddo & Michelle Bachler

We report on progress made during the collaboration between KMi's Hypermedia Discourse Group and Ágnes Sándor (Xerox Research Centre Europe, Parsing & Semantics Group). This is the outcome of her 6 week OLnet Project Expert Fellowship at the OU, funded by the Hewlett Foundation, to develop Collective Intelligence for the Open Educational Resources (OER) community.

Our research investigates the overlaps and complementarities between the outputs from human analysts making sense of 120 OER project reports, using KMi's Cohere semantic annotation and knowledge mapping tool, and machine annotation of the corpus by the Xerox Incremental Parser (XIP). XIP's output is imported into Cohere to explore ways to visualize the combined human+machine output, and we present preliminary results from interviews with some of the analysts to elicit their views on XIP's annotations.

PDF verson of the slides available here.

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.