 However, alignment-based approaches are inferior to the generic sentence vectorsin terms of performance. We hypothesize that the reason for the inferiority of alignment-based methods is due to the fact that they do not distinguish word importance and word meaning.
<meaning-changed>  However, alignment-based approaches are inferior to the generic sentence vectorsin terms of performance. We hypothesize that the reason for the inferiority of alignment-based methods is due to the fact that they do not distinguish word importance and word meaning.
 However, alignment-based approaches are inferior to the simple cosine similarity between general-purpose sentence vectors. To remedy this, we focus on the fact that the norm of word vectors is a good proxy for word importance, and the angle of them is a good proxy for word similarity. Alignment-based approaches do not distinguish word importance and word meaning.