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To start, you would need to generate the dataset using the script inside IstexDataDownload_Treatment folder (you may also dowload it from:
https://drive.google.com/drive/folders/1i1I3fi6Qgdz-A4hI8_MkjZCg-EPieTi_?usp=sharing
) -
The main file to start with is bow_svd.py. It will transform the whole corpus into its semantic features representation.
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Then, run classifier.py to train and to generate ranked results.
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The baseline is using More_Like_This Query of ElasticSearch.
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You can find the users annotations in the annotations folder. The notebook comparatrive_evaluation.ipynb provide the initial evaluation
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For active learning process, you should open and run the cells of build_dataset_active_learning.ipynb
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You may also check other available notebooks for further analysis. Other .py files like LDA for topic analysis are also available
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Semantic Search-by-Examples and Topic-Tagging for Scietific Domain Expansion in Digital Lbraries
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