KMi Seminars
Wisdom of Crowds vs. Wisdom of Linguists
This event took place on Wednesday 08 December 2010 at 11:30

 
Dr. Torsten Zesch Ubiquitous Knowledge Processing lab, TU Darmstadt, Germany

Computing the semantic relatedness between words is a pervasive task in natural language processing. So far, insufficient coverage of linguistic knowledge resources has been a major impediment for using semantic relatedness measures in large-scale applications. Recently, rapidly growing collaboratively constructed resources like Wikipedia and Wiktionary have been discovered as a new kind of semantic resource.

In the talk, I will shortly introduce these new resources and show how existing semantic relatedness measures can be adapted to the new resources. I will then compare the performance of traditional resources (Wisdom of Linguists) with that of the new resources (Wisdom of Crowds), and show under which conditions collaboratively constructed semantic resources can be used as a proxy for linguistically constructed semantic resources.

Additionally, I will introduce freely available application programming interfaces to Wikipedia and Wiktionary that have been used to conduct the experiments described in my talk.

 
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.