Text Classification Using Association Rules, Dependency Pruning and Hyperonymization
Table 2d Strategy I2: Pruning by keeping only nouns at distance 1 from head
['[EMPTY]', 'E12', 'GCRIM', 'GDIP', 'GJOB', 'GPOL', 'GSPO', 'GVIO', 'AVG']
Note that the slightly higher than 1 transaction size is probably due to the rare cases where there are more than one nsubj dependencies pointing to the head. The scores rise dramatically when compared to those of the strategy based only on the head of the sentence. The average F-measure (71.80%) is significantly higher than the tfidf-based performance for the same average transaction size (65.69%). This shows that using a dependency property to select a word is a better choice than the one provided by the frequentist tfidf-based method.