In the first week, I have defined an idea of how the integration of AppRecommender and AppStream will work. I have contacted the AppStream team with the idea, that can be seen in the following link:
Also the links for AppRecommender and my AppStream repository can be seen bellow:
Furthermore, this week I have also started to package AppRecommender, but there was a problem with one of the packages dependencies, python-nltk. AppRecommender has been using the stopwords and stemming libraries from python-nltk for some recommendation strategies. However, they are not present when the package is installed, requiring them to be downloaded separately. In order to solve that, I have removed python-nltk from AppRecommender and replaced it by python-stemmer, which has the same stemming algorithm that AppRecommender was using with python-nltk.
For the next week, My mentors and I have defined the following tasks:
* Create a recommendation class on AppStream:
* Create parser for recommendation XML file:
* Continue AppRecommender package:
It must also be said that depending on the feedback from the AppStream community on my idea, new issues for this week will arise.