Abstract
ThisThis work is licensed under a Creative Commons Attribution 4.0 International Licence. Page numbers and proceedings footer are added by the organisers. Licence details: http://creativecommons.org/licenses/by/4.0/paper describes the second version of the ASAP system and its participation in the SemEval-2015, task 2a on Semantic Textual Similarity (STS). Our approach is based on computing the WordNet semantic relatedness and similarity of phrases from distinct sentences. We also apply topic modeling to get topic distributions over a set of sentences as well as some linguistic heuristics. In a special addition for this task, we retrieve named entities and compound nouns from DBPedia. All these features are used to feed a regression algorithm that learns the STS function.
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CITATION STYLE
Alves, A. O., Simões, D., Oliveira, H. G., & Ferrugento, A. (2015). ASAP-II: From the Alignment of Phrases to Text Similarity. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 184–189). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2033
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