MathLingBudapest: Concept Networks for Semantic Similarity

We present our approach to measuring semantic similarity of sentence pairs used in Semeval 2015 tasks 1 and 2. We adopt the sentence alignment framework of (Han et al., 2013) and experiment with several measures of word similarity. We hybridize the common vector-based models with definition graphs from the 4lang concept dictionary and devise a measure of graph similarity that yields good results on training data. We did not address the specific challenges posed by Twitter data, and this is reflected in placing 11th from 30 in Task 1, but our systems perform fairly well on the generic datasets of Task 2, with the hybrid approach placing 11th among 78 runs.