By Veselin Rakocevic, Katarina Stanoevska-Slabeva, Luigi Telesca
This quantity includes the court cases of the 1st foreign ICST convention on electronic company (DigiBiz 2009), hosted through urban collage London in London, united kingdom. This annual occasion had the most goal to stimulate and disseminate study effects and experimentation on destiny electronic company to a much wider multidisciplinary discussion board that might permit the individuals to move the bounds among examine and enterprise. The medical delivering in e-business, e-commerce, and ICT regularly is kind of wide and spans many various examine topics, regarding a number of groups and me- odologies. the expansion and dynamic nature of those learn topics pose either ch- lenges and possibilities. The demanding situations are in having scientists and practitioners check with one another: although they paintings on related difficulties they generally use very various languages when it comes to study instruments and techniques. The possibilities nonetheless come up whilst scientists and practitioners have interaction in multidisciplinary d- cussions resulting in new principles, tasks and items.
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Extra resources for Digital Business: First International ICST Conference, DigiBiz 2009, London, UK, June 17-19, 2009, Revised Selected Papers (Lecture Notes of the Institute ... and Telecommunications Engineering)
Example text
3. Requirements Analysis Strategy The process of analysing user requirements in SPIKE starts with the activity stated in the lower left corner of Fig. 2) shown in the upper right corner. Enabling several iterations to refine and update the achieved results, the requirements analysis is rather a lifecycle than a process. Throughout the lifecycle, use cases and market research are important elements for analysing the requirements. Each single requirement must pass a quality gateway and is reviewed during workshops.
We model a user using a workflow which encodes the sequence of actions to be executed; in particular, we define three functions, the pref function, the shape function and the like function, which encode the user’s preferences and decision making procedures. While pref and like functions are supposed to be stationary and defined at the beginning of the negotiation, shape is conceived A Recommender for Active Preference Estimate 21 as an adaptive function whose definition evolves through the negotiation by a process of learning.
Another effect of this simple scenario is that the number of answers of type DISLIKE one obtains is very low (once discovered the right feature, being it binary, there is an high probability of ending the negotiation), and the computation of the relevance is deeply affected by it. Another interesting results is the comparison of the speed in obtaining a successful negotiation. In Figure 1 we show, in the left part, the histograms of the mean counts of successfull negotiations with the random strategy and with the AOS recommender.