Difference between revisions of "DAO"
From Knoesis wiki
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==== Automatic Qualitative Coding ==== | ==== Automatic Qualitative Coding ==== | ||
| − | This is the most challenging aspect of[http://wiki.knoesis.org/index.php | + | This is the most challenging aspect of[http://wiki.knoesis.org/index.php/ PREDOSE]. The aim is to use various information extraction techniques to extraction semantic information considered semantically equivalent to qualitative codes, from web forums. Types of extracted information include: |
#''' Drug Abuse Ontology (DAO):''' We manually created a Drug Abuse Ontology (DAO) to model the prescription drug abuse domain, which is the first ontology on drug abuse in the literature. The current DAO is available [http://knoesis-hpco.cs.wright.edu/drug-abuse-ontology/ online]. The DAO is used to facilitate search, and it also serves as the annotation scheme for the entity, relationship and triple extraction. <br /> | #''' Drug Abuse Ontology (DAO):''' We manually created a Drug Abuse Ontology (DAO) to model the prescription drug abuse domain, which is the first ontology on drug abuse in the literature. The current DAO is available [http://knoesis-hpco.cs.wright.edu/drug-abuse-ontology/ online]. The DAO is used to facilitate search, and it also serves as the annotation scheme for the entity, relationship and triple extraction. <br /> | ||
Revision as of 23:05, 24 July 2017
DAO is the acronym for Drug Abuse Ontology.
The PREDOSE research team at Knoesis has developed preliminary techniques that automatically extract semantic information from Web-based data. Such includes entities, generic sentiment expressions, relationships and triples. To perform entity identification, the research team relies on a combination of lexical and semantics-based techniques, based on a manually curated Drug Abuse Ontology (DAO) - pronounced dow), which is the first ontology for prescription drug abuse.
Automatic Qualitative Coding
This is the most challenging aspect ofPREDOSE. The aim is to use various information extraction techniques to extraction semantic information considered semantically equivalent to qualitative codes, from web forums. Types of extracted information include:
- Drug Abuse Ontology (DAO): We manually created a Drug Abuse Ontology (DAO) to model the prescription drug abuse domain, which is the first ontology on drug abuse in the literature. The current DAO is available online. The DAO is used to facilitate search, and it also serves as the annotation scheme for the entity, relationship and triple extraction.
