FCICU: The Integration between Sense-Based Kernel and Surface-Based Methods to Measure Semantic Textual Similarity
Basma Mohammed Hassan, Samir E. Abdelrahman, Reem Bahgat · 2015
This paper describes FCICU team participation in SemEval 2015 for Semantic Textual Similarity challenge.Our main contribution is to propose a word-sense similarity method using BabelNet relationships.In the English subtask challenge, we submitted three systems (runs) to assess the proposed method.In Run1, we used our proposed method coupled with a string kernel mapping function to calculate the textual similarity.In Run2, we used the method with a tree kernel function.In Run3, we averaged Run1 with a previously proposed surface-based approach as a kind of integration.The three runs are ranked 41 st , 57 th , and 20 th of 73 systems, with mean correlation 0.702, 0.597, and 0.759 respectively.For the interpretable task, we submitted a modified version of Run1 achieving mean F1 0.846, 0.461, 0.722, and 0.44 for alignment, type, score, and score with type respectively.