The strength of the system and my experiences of it, was that in fact, oddly enough, it was actually a very collaborative enterprise already

Video:35 mins, 2006. The video shows a group of performers in a studio and seminar situation. Individually addressing the camera they offer personal views and experiences of their own art production in relation to the institution, while reflecting on their role as teachers. The performance scripts mainly originate from a series of real interviews with a diverse group of artist teachers, who emphasise the collaborative, performative and subversive nature of teaching. These views may seems symptomatic for contemporary art practices, but are ultimately antagonistic to the ongoing commodification of the system of art education.

Collaborative personal profiling for web service ranking and recommendation

Web service is one of the most fundamental technologies in implementing service oriented architecture (SOA) based applications. One essential challenge related to web service is to find suitable candidates with regard to web service consumer’s requests, which is normally called web service discovery. During a web service discovery protocol, it is expected that the consumer will find it hard to distinguish which ones are more suitable in the retrieval set, thereby making selection of web services a critical task. In this paper, inspired by the idea that the service composition pattern is significant hint for service selection, a personal profiling mechanism is proposed to improve ranking and recommendation performance. Since service selection is highly dependent on the composition process, personal knowledge is accumulated from previous service composition process and shared via collaborative filtering where a set of users with similar interest will be firstly identified. Afterwards a web service re-ranking mechanism is employed for personalised recommendation. Experimental studies are conduced and analysed to demonstrate the promising potential of this research.