HulTech: A General Purpose System for Cross-Level Semantic Similarity based on Anchor Web Counts

Abstract

This paper describes the HULTECH team participation in Task 3 of SemEval-2014. Four different subtasks are provided to the participants, who are asked to determine the semantic similarity of cross-level test pairs: paragraphto-sentence, sentence-to-phrase, phrase-toword and word-to-sense. Our system adopts a unified strategy (general purpose system) to calculate similarity across all subtasks based on word Web frequencies. For that purpose, we define ClueWeb InfoSimba, a cross-level similarity corpus-based metric. Results show that our strategy overcomes the proposed baselines and achieves adequate to moderate results when compared to other systems.