Hi,all: In the past two weeks, the major work is to mine user interest via observing user behavior in the gpodder. I try to record top score keywords of one episode which user chooses to download in the behavior model. Then use a mining algorithm to pick up top-n keywords from this model to populate the user profile.
I also tried to re-design the recommendation score algorithm. I want to use new social tag feature in opencalais to score each episode. I think until now, the basic work of recommendation has been done. In the next phase, I would focus on the context-aware module which will not only be in charge of user-awareness but also be aware of device and environment context. I will try to design a framework to implement basic functions and then other developers can easily use this framework to add context-aware funtions into their applications. In the next two weeks, I will do some paper works. I will document the new score algorithm and the framework. At the same time , I will fix some bugs in current code then release a new version of gpodder , then get some feedbacks from the community. If you are interested in my project, then you can find much more information on http://garage.maemo.org/projects/newssprite. You can also check out the code on the svn repository. Any comments and suggestions are welcome.Thanks. -- --Feng GAO --Maemo-GSoC09
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