We combine several graph alignment features with lexical semantic similarity measures using machine learning techniques and show that the student answers can be more accurately graded than if the semantic measures were used in isolation.

Of these, 36 are based upon the semantic similarity

3.3 Lexical Semantic Similarity

In order to address this, we combine the graph alignment scores, which encode syntactic knowledge, with the scores obtained from semantic similarity measures.

All of these vectors capture broad semantic similarities .

To capture semantic similarities among words, we derive a probabilistic model of documents which learns word representations.

3.1 Capturing Semantic Similarities