Difference between revisions of "Machine Learning biotml"

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(Created page with "__TOC__ == About BioTML Plug-in == This is a Machine learning based plug-in that ... == Install Plug-in == How to Install == User HowTOs == ==...")
 
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== About BioTML Plug-in ==
 
== About BioTML Plug-in ==
  
This is a Machine learning based plug-in that ...
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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.  
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These models can be used in a prediction stage to annotate documents from a selected @Note corpus.
  
 
== Install Plug-in ==
 
== Install Plug-in ==
  
[[BioTML_Install_Plug-in|How to Install]]
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The BioTML can be installed as any other plugin following the instructions available in:
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[[Add_New_Plugin|How to Install]]
  
 
== User HowTOs ==
 
== User HowTOs ==
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[[NER_Model_Creation | NER Model Creation]]
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[[RE_Model_Creation | RE Model Creation]]
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[[Corpus_Create_Annotation_Schema_By_BioTML_Tagger | NER Annotation of documents using machine learning models]]
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[[Corpus_Relation_Extraction_By_BioTML_Tagger | RE Annotation of documents using machine learning models]]
  
 
== MVC AIBench Model: ==
 
== MVC AIBench Model: ==
  
 
=== '''''Operations:''''' ===
 
=== '''''Operations:''''' ===
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'''''CreateNERModelFile''''': Creates a BioTML NER model file using an existent NERProcess for novel entity identification in other corpus.
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'''''CreateREModelFile''''': Creates a BioTML RE model file using an existent REProcess for novel relations identification in other corpus.
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'''''AnnotateCorpusWithNERModel''''': Apply the NER Process to Corpus based in the provided machine learning model prediction for entity identification.
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'''''AnnotateCorpusWithREModel''''': Apply the RE Process to Corpus based in the provided machine learning model prediction  associated with an existent NERProcess for entity identification.

Latest revision as of 14:15, 4 August 2015

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:

How to Install

User HowTOs

NER Model Creation

RE Model Creation

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.