Our experiments are designed to explore two main questions: (a) the value of symmetric patterns as semantic classification features, compared to state-of-the-art word clustering and embedding methods; and (b) the required complexity of an algorithm that can propagate information about semantic similarity.
we test the value of our simple I-k-NN algorithm compared to more sophisticated alternatives.