QASSIT at SemEval 2016 Task 13: On the integration of Semantic Vectors in Pretopological Spaces for Lexical Taxonomy Acquisition
This paper presents our participation to the SemEval "Task 13: Taxonomy Extraction Evaluation (TExEval 2)" (Bordea et al. 2016) This year, we propose the combination of recent semantic vectors representation into a methodology for semisupervised and auto supervised acquisition of lexical taxonomies from raw texts. In our proposal, first similarities between concepts are calculated using semantic vectors, then a pretopological space is defined from which a preliminary structure is constructed. Finally, a genetic algorithm is used to optimize two different functions, the quality of the added relationships in the taxonomy and the quality of the structure. Experiments show that our proposal has a competitive performance when compared with the other participants achieving the second position in the general rank.
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