Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study
Table 3: Accuracy of tree-kernel-based any-grams Kaljahi-Foster-PEOPLES-2016 (NGT prefix), any-gram kernels introduced here (AGK prefix) and LSTM models (LSTM suffix) for various settings, on SE14 and SSTB data sets
['[EMPTY]', 'Laptop Dev', 'Laptop Test', 'Restaurant Dev', 'Restaurant Test', 'SSTB Dev', 'SSTB Test']
Systems in the first and second rows of the table, with their names starting with NGTK, are the ones based on tree-kernel-based any-grams and those in the middle section of the table, with their names starting with AGK, are the ones built using the new any-gram kernels. The last two rows in the table are for the LSTM models. The sm suffix stands for string match, the west for word embedding similarity threshold and the wess for word embedding similarity score.