1. A computer-implemented method for determining semantically related terms, the method comprising: receiving a first plurality of semantically related terms from a keyword suggestion tool; presenting at least a portion of the terms of the first plurality of semantically related terms to a user based on a predictive error of each term of the first plurality of semantically related terms, wherein a predictive error of a term is calculated using the equation: where x is a term vector associated with a term of the first plurality of semantically related terms and X is a matrix including a term vector for each term of the first plurality of semantically related terms; receiving an indication of relevance of at least one of the terms presented to the user from the first plurality of semantically related terms; training a model to predict an indication of relevance of a term by the user based on the received indication of relevance of at least one of the terms presented to the user from the first plurality of semantically related terms; receiving a second plurality of semantically related terms from the keyword suggestion tool; and presenting at least a portion of the terms of the second plurality of semantically related terms to the user based on the model and one or more properties of each term of the second plurality of semantically related terms, wherein the one or more properties of each term of the second plurality of semantically related terms includes at least prefix overlap.