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. 2015 Apr 8;16:113. doi: 10.1186/s12859-015-0539-7

Table 6.

Feature combination results

SVM-perf Ada over
Feature combination Prec Rec F1 Prec Rec F1
Unigram 0.395 0.654 0.492 0.528 0.425 0.471
Unigram+CUI 0.409 0.657 0.504* 0.529 0.437 0.479*
Unigram+Meta 0.387 0.672 0.491 0.550 0.405 0.466
Unigram+NP 0.382 0.701 0.495* 0.535 0.424 0.473
Unigram+Taxo 0.403 0.660 0.500* 0.531 0.432 0.477
Unigram+mti 0.448 0.679 0.540* 0.586 0.477 0.526*
Unigram+mmi+prc 0.445 0.677 0.537* 0.583 0.474 0.523*
Unigram+all 0.452 0.689 0.546* 0.600 0.476 0.531*
Feature combination Prec Rec F1 Prec Rec F1
TIAB+bigram 0.408 0.685 0.512 0.556 0.421 0.479
TIAB+bigram+CUI 0.439 0.688 0.536 0.556 0.435 0.488*
TIAB+bigram+Meta 0.408 0.689 0.513 0.581 0.406 0.478
TIAB+bigram+NP 0.417 0.686 0.518* 0.560 0.422 0.481
TIAB+bigram+Taxo 0.418 0.679 0.518* 0.554 0.412 0.472
TIAB+bigram+mti 0.451 0.701 0.549* 0.604 0.475 0.532*
TIAB+bigram+mmi+prc 0.448 0.699 0.546* 0.607 0.466 0.528*
TIAB+bigram+all 0.470 0.682 0.557* 0.629 0.380 0.474

Results are reported in Precision (Prec), Recall (Rec) and F-measure (F1). Unigrams and bigrams with feature source (either title or abstract, TIAB+bigram) are combined with concepts identifiers (+CUI), meta-data (+Meta), noun phrases (+NP), hypernyms (+Taxo), MTI predictions (+mti), MTI components (mti+prc) and all the features (+all). For each column, results significantly better (p >0.05) than the ones obtained with unigram or TIAB+bigram are indicated with *.