Difference between revisions of "Machine Learning biotml"
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[[Corpus_Create_Annotation_Schema_By_BioTML_Tagger | NER Annotation of documents using machine learning models]] | [[Corpus_Create_Annotation_Schema_By_BioTML_Tagger | NER Annotation of documents using machine learning models]] | ||
| − | [[Corpus_Relation_Extraction_By_BioTML_Tagger | + | [[Corpus_Relation_Extraction_By_BioTML_Tagger | RE Annotation of documents using machine learning models]] |
== MVC AIBench Model: == | == MVC AIBench Model: == | ||
Latest revision as of 14:15, 4 August 2015
Contents
About BioTML Plug-in
BioTML is a Machine learning based plug-in that enables users to create models, trained based on available annotations (NER or RE) created by the user using the manual curation environment. These models can be used in a prediction stage to annotate documents from a selected @Note corpus.
Install Plug-in
The BioTML can be installed as any other plugin following the instructions available in:
User HowTOs
NER Annotation of documents using machine learning models
RE Annotation of documents using machine learning models
MVC AIBench Model:
Operations:
CreateNERModelFile: Creates a BioTML NER model file using an existent NERProcess for novel entity identification in other corpus.
CreateREModelFile: Creates a BioTML RE model file using an existent REProcess for novel relations identification in other corpus.
AnnotateCorpusWithNERModel: Apply the NER Process to Corpus based in the provided machine learning model prediction for entity identification.
AnnotateCorpusWithREModel: Apply the RE Process to Corpus based in the provided machine learning model prediction associated with an existent NERProcess for entity identification.
