ESBM: An Entity Summarization BenchMark
Table 5: F1 of RandomForest after removing each individual feature, its difference from using all features (Δ%), and the significance level for the difference (p).
['DBpedia  [ITALIC] k=5', 'DBpedia  [ITALIC] k=5', 'DBpedia  [ITALIC] k=5', 'DBpedia  [ITALIC] k=5', 'DBpedia  [ITALIC] k=10', 'DBpedia  [ITALIC] k=10', 'DBpedia  [ITALIC] k=10', 'DBpedia  [ITALIC] k=10', 'LinkedMDB  [ITALIC] k=5', 'LinkedMDB  [ITALIC] k=5', 'LinkedMDB  [ITALIC] k=5', 'LinkedMDB  [ITALIC] k=5', 'LinkedMDB  [ITALIC] k=10', 'LinkedMDB  [ITALIC] k=10', 'LinkedMDB  [ITALIC] k=10', 'LinkedMDB  [ITALIC] k=10']
Moreover, we are interested in how much the seven features contribute to the good performance of supervised learning. Considering statistical significance at the 0.05 level, two features gfT and lf show effectiveness on both datasets under both size constraints, and two features vfT and si are only effective on LinkedMDB. The usefulness of the three binary features isC, isE, and isL is not statistically significant.