CPN-CORE: A Text Semantic Similarity System Infused with Opinion Knowledge
Carmen Banea, Yoonjung Choi, Lingjia Deng, Samer Hassan, Michael Mohler, Bishan Yang, Claire Cardie, Rada F. Mihalcea, Jan Wiebe, Google Inc · 2013
This article provides a detailed overview of the CPN text-to-text similarity system that we participated with in the Semantic Textual Similarity task evaluations hosted at *SEM 2013. In addition to more traditional components, such as knowledge-based and corpus-based metrics leveraged in a machine learning framework, we also use opinion analysis features to achieve a stronger semantic representation of textual units. While the evaluation datasets are not designed to test the similarity of opinions, as a component of textual similarity, nonetheless, our system variations ranked number 38, 39 and 45 among the 88 participating systems. 1