CoCoScore: context-aware co-occurrence scoring for text mining applications using distant supervision.

ABSTRACT:

Motivation

Information extraction by mining the scientific literature is key to uncovering relations between biomedical entities. Most existing approaches based on natural language processing extract relations from single sentence-level co-mentions, ignoring co-occurrence statistics over the whole corpus. Existing approaches counting entity co-occurrences ignore the textual context of each co-occurrence.

Results

We propose a novel corpus-wide co-occurrence scoring approach to relation extraction that takes the textual context of each co-mention into account. Our method, called CoCoScore, scores the certainty of stating an association for each sentence that co-mentions two entities. CoCoScore is trained using distant supervision based on a gold-standard set of associations be

SUBMITTER: Junge A 

PROVIDER: S-EPMC6956794 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature