Avoiding background knowledge: literature based discovery from important information.

ABSTRACT:

Background

Automatic literature based discovery attempts to uncover new knowledge by connecting existing facts: information extracted from existing publications in the form of [Formula: see text] and [Formula: see text] relations can be simply connected to deduce [Formula: see text]. However, using this approach, the quantity of proposed connections is often too vast to be useful. It can be reduced by using subject[Formula: see text](predicate)[Formula: see text]object triples as the [Formula: see text] relations, but too many proposed connections remain for manual verification.

Results

Based on the hypothesis that only a small number of subject-predicate-object triples extracted from a publication represent the paper's novel contribution(s), we explore using BERT embeddings

SUBMITTER: Preiss J 

PROVIDER: S-EPMC10013236 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature