Papers › A graph kernel based on context vectors for extracting drug–drug interactions
A graph kernel based on context vectors for extracting drug–drug interactions
Wei Zheng, Hongfei Lin, Zhehuan Zhao, Bo Xu, Yijia Zhang, Zhihao Yang, Jian Wang
The clinical recognition of drug–drug interactions (DDIs) is a crucial issue for both patient safety and health care cost control. Thus there is an urgent need that DDIs be extracted automatically from biomedical literature by text-mining techniques. Although the top-ranking DDIs systems explore various features of texts, these features can’t yet adequately express long and complicated sentences. In this paper, we present an effective graph kernel which makes full use of different types of contexts to identify DDIs from biomedical literature. In our approach, the relations among long-range words, in addition to close-range words, are obtained by the graph representation of a parsed sentence. Context vectors of a vertex, an iterative vectorial representation of all labeled nodes adjacent and nonadjacent to it, adequately capture the direct and indirect substructures’ information. Furthermore, the graph kernel considering the distance between context vectors is used to detect DDIs. Experimental results on the DDIExtraction 2013 corpus show that our system achieves the best detection and classification performance (F-score) of DDIs (81.8 and 68.4, respectively). Especially for the Medline-2013 dataset, our system outperforms the top-ranking DDIs systems by F-scores of 10.7 and 12.2 in detection and classification, respectively.
Code
No code repository is listed for this paper in the archive or in Syntology's graph.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Drug–drug Interaction Extraction | DDI extraction 2013 corpus | Graph Kernel-based method | F1 | 0.684 | #7 of 10 | Archive leaderboard | report |
| Drug–drug Interaction Extraction | DDI extraction 2013 corpus | Graph Kernel-based method | Micro F1 | 68.4 | #7 of 10 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections