Infobox suggestion for Wikipedia entities.

Given the sheer amount of work and expertise required in authoring Wikipedia articles, automatic tools that help Wikipedia contributors in generating and improving content are valuable. This paper presents our initial step towards building a full-fledged author assistant, particularly for suggesting infobox templates for articles. We build SVM classifiers to suggest infobox template types, among a large number of possible types, to Wikipedia articles without infoboxes. Different from prior works on Wikipedia article classification which deal with only a few label classes for named entity recognition, the much larger 337-class setup in our study is geared towards realistic deployment of infobox suggestion tool. We also emphasize testing on articles without infoboxes, due to that labeled and unlabeled data exhibit different distributions of features, which departs from the typical assumption that they are drawn from the same underlying population.