This is a collection of code written by Maurice Curran that was used to process the Microscopy and Microanalysis conference proceeding corpus into word products described in the publication "NLP-Driven Electron Microscopy Ontology Development". The scripts are written in Python, to be used in the following order:1. SettingUpTextFiles.py and CopyingText.py to get the raw text files; 2. SentenceConversion.py; 3. reference_remover.py; 4. testing.py and testingavg.py; 5. SentenceCreator.py; 6. matscholar_model.py to get matscholar tags; 7. training_model_gensim.py to get gensim model;8. word2vecscript.py and gensim_visual.py;
About this Dataset
| Title | Code used to produce terms list in the work "NLP-Driven Electron Microscopy Ontology Development" |
|---|---|
| Description | This is a collection of code written by Maurice Curran that was used to process the Microscopy and Microanalysis conference proceeding corpus into word products described in the publication "NLP-Driven Electron Microscopy Ontology Development". The scripts are written in Python, to be used in the following order:1. SettingUpTextFiles.py and CopyingText.py to get the raw text files; 2. SentenceConversion.py; 3. reference_remover.py; 4. testing.py and testingavg.py; 5. SentenceCreator.py; 6. matscholar_model.py to get matscholar tags; 7. training_model_gensim.py to get gensim model;8. word2vecscript.py and gensim_visual.py; |
| Modified | 2021-12-31 00:00:00 |
| Publisher Name | National Institute of Standards and Technology |
| Contact | mailto:[email protected] |
| Keywords | Natural language processing , NLP , electron microscopy , controlled vocabulary , ontology |
{
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"contactPoint": {
"hasEmail": "mailto:[email protected]",
"fn": "June W. Lau"
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"landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3198",
"title": "Code used to produce terms list in the work \"NLP-Driven Electron Microscopy Ontology Development\"",
"description": "This is a collection of code written by Maurice Curran that was used to process the Microscopy and Microanalysis conference proceeding corpus into word products described in the publication \"NLP-Driven Electron Microscopy Ontology Development\". The scripts are written in Python, to be used in the following order:1. SettingUpTextFiles.py and CopyingText.py to get the raw text files; 2. SentenceConversion.py; 3. reference_remover.py; 4. testing.py and testingavg.py; 5. SentenceCreator.py; 6. matscholar_model.py to get matscholar tags; 7. training_model_gensim.py to get gensim model;8. word2vecscript.py and gensim_visual.py;",
"language": [
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"distribution": [
{
"downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-3198\/PythonFiles_Maurice_clean.zip",
"description": "This zip file contains a set of scripts that extracts frequently occurring words from the conference proceedings of Microscopy & Microanalysis between the years of 2002 and 2019.",
"mediaType": "application\/zip",
"title": "NLP code to produce words about electron microscopy"
}
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"modified": "2021-12-31 00:00:00",
"publisher": {
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"name": "National Institute of Standards and Technology"
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"theme": [
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"Materials:Modeling and computational material science",
"Materials:Materials characterization"
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"keyword": [
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"NLP",
"electron microscopy",
"controlled vocabulary",
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}