Semantic Similarity Graphs of Mathematics Word Problems: Can Terminology Detection Help?

Curricula often lack metadata to characterize the relatedness of concepts. To investigate automatic methods for generating relatedness metadata for a mathematics curriculum, we first address the task of identifying which terms in the vocabulary from mathematics word problems are associated with the curriculum. High chance-adjusted interannotator agreement on manual identification of math terms was achieved by considering terms in their contexts. These terms represent 13% of the vocabulary in one seventh grade mathematics text. Six classification algorithms were compared to classify math terms for this text. To avoid overfitting to this curriculum, we relied on a small number of features that exploit external knowledge sources.