Metadata-Version: 2.1
Name: argument-esa-model
Version: 3.11.49
Summary: An ESA implementation in python.
Home-page: https://git.webis.de/args/args-topic-modeling/tree/master/src/python/esa
Author: Yamen Ajjour
Author-email: yajjour@hotmail.com
License: UNKNOWN
Description: # Get the required resources
        <code> scp -r webis@webislab40.medien.uni-weimar.de:/home/weci2587/projects/args-topic-modeling/resources . </code>
        
        # 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.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
