Get the required resources
scp -r webis@webislab40.medien.uni-weimar.de:/home/weci2587/projects/args-topic-modeling/resources .
To run the ESA-script with all terms run:
For normal ESA:
./esa-all-terms.py --similarity cos
--matrix-path <path_to_resources>/resources/esa-plain/<debatepedia|strategic-intelligence|wikipedia>.mat
--model-path <path_to_resources>/resources/esa-w2v/GoogleNews-vectors-negative300.bin
--model-vocab <path_to_resources>/resources/esa-w2v/w2v-vocab.p
--input-path <path_to_input_file>
--output-path <path_to_output_file>
For word2vec-ESA:
./esa-all-terms.py --similarity max
--matrix-path <path_to_resources>/resources/esa-w2v/<debatepedia|strategic-intelligence|wikipedia>.mat
--model-path <path_to_resources>/resources/esa-w2v/GoogleNews-vectors-negative300.bin
--model-vocab <path_to_resources>/resources/esa-w2v/w2v-vocab.p
--input-path <path_to_input_file>
--output-path <path_to_output_file>
To run the word2vec-ESA with reduced terms run:
./esa-top-n-terms.py -n <number_of_terms>
--corpus-path <path_to_resources>/resources/corpora/<debatepedia|strategic-intelligence|wikipedia>.csv
--model-path <path_to_resources>/resources/esa-w2v/GoogleNews-vectors-negative300.bin
--model-vocab <path_to_resources>/resources/esa-w2v/w2v-vocab.p
--input-path <path_to_input_file>
--output-path <path_to_output_file>
The input document must be a csv file with "|" as the separator and must contain the column "document", which is used as the input text for the ESA.
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Metadata
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Release files for argument-esa-model 3.11.112
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