By Leila Zia

Only 1% of English Wikipedia articles are labeled with quality class Good or better, and 37% of the articles are stubs. We are building an article expansion recommendation system to change this in Wikipedia, across many languages. In this presentation, I will talk with you about our current thinking of the vision and direction of the research that can help us build such a recommendation system, and share more about one specific area of research we have heavily focused on in the past months: building a recommendation system that can help editors identify what sections to add to an already existing article. I present some of the challenges we faced, the methods we devised or used to overcome them, and the result of the first line of experiments on the quality of such recommendations (teaser: the results are really promising. The precision and recall at 10 is 80%.)