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Information


Unique identifier OMICS_05552
Name DDI Corpus
Restrictions to use None
Community driven No
Data access File download
User data submission Not allowed
Content license CC Attribution-NonCommercial-ShareAlike
Maintained No

Documentation


Publication for DDI Corpus

DDI Corpus citations

 (7)
library_books

Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning

2016
PMCID: 4834204
PMID: 27087307
DOI: 10.1093/database/baw049

[…] EBI (). To enlarge the training dataset for patent chemical NER, several studies leveraged the corpora from other resources, such as the CHEMDNER corpus built from biomedical literature (, ), and the DDI corpus (, ) built from both DrugBank and biomedical literature. As seen in literature, the major approaches for building chemical NER systems for patent text were dictionary lookup (, , , ) and ma […]

library_books

Drug Drug Interaction Extraction via Convolutional Neural Networks

2016
PMCID: 4752975
PMID: 26941831
DOI: 10.1155/2016/6918381

[…] The CNN-based DDI extraction system is developed and evaluated on the DDI corpus of the 2013 DDIExtraction challenge [], which is composed of 730 DrugBank documents and 175 MEDLINE abstracts about DDIs. The corpus is split into two parts: a training set (572 DrugBank do […]

library_books

ChemTok: A New Rule Based Tokenizer for Chemical Named Entity Recognition

2016
Biomed Res Int
PMCID: 4749772
PMID: 26942193
DOI: 10.1155/2016/4248026

[…] ion algorithm correctly segments at affixes resulting in a positive effect on the entities belonging to the “Family” class in the BioCreative data set and entities in the “Group” class in the SemEval DDI corpus. Step  2.2 of the algorithm ensures that tokens which are already known are not further tokenized improving the tokenization performance of the mentioned entities in the “Trivial” class and […]

library_books

Extraction of Pharmacokinetic Evidence of Drug–Drug Interactions from the Literature

2015
PLoS One
PMCID: 4427505
PMID: 25961290
DOI: 10.1371/journal.pone.0122199

[…] ls and dictionaries, with dictionary matches identified by internally-developed software. A preliminary study of the impact of NER/Dictionary features was reported in [] using a previous less-refined DDI corpus. Here, in addition to using the more fine-tuned corpus (see “Methods and Data” section), we study the impact of PubMed metadata features on classification performance. We also provide a new […]

call_split

Improving chemical entity recognition through h index based semantic similarity

2015
J Cheminform
PMCID: 4331689
PMID: 25810770
DOI: 10.1186/1758-2946-7-S1-S13
call_split See protocol

[…] on was useful to adjust the precision of our predictions, and to rank them according to how confident the system is about the extracted mention being correct.We used the provided CHEMDNER corpus, the DDI corpus and the patents corpus for training multiple CRF classifiers, based on the different types of entities considered on each dataset. Each title and abstract from the test set was classified w […]

library_books

An analysis on the entity annotations in biological corpora

2014
F1000Res
PMCID: 4168744
PMID: 25254099
DOI: 10.5256/f1000research.3456.r4561

[…] , which focused initially on the IUPAC nomenclature. But this has become a hot topic in the last couple of years and following corpora have provided annotations also for drugs and their interactions (DDI corpus), as well as anotations on full text documents (CRAFT corpus). The CHEMDNER corpus classifies chemicals in some predefined categories and was used in the one of the shared tasks in last Bio […]

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DDI Corpus institution(s)
Computer Science Department, Universidad Carlos III de Madrid, Madrid, Spain; German Research Center for Artificial Intelligence, DFKI GmbH Language Technology Lab, Saarbrücken, Germany
DDI Corpus funding source(s)
This work was supported by the EU project TrendMiner [FP7-ICT287863], by the project MULTIMEDICA [TIN2010-20644-C03-01], and by the Research Network MA2VICMR [S2009/TIC-1542].

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