Formal concept analysis for topic detection: a clustering quality experimental analysis
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'FCA.tar.gz (about 3MB)This file contains the FCA implementation as well as the input files for the executionThe dataset can be downloaded from the official RepLab webpage: http://nlp.uned.es/replab2013/' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Clustering quality analysis","Formal concept analysis","Hierarchical agglomerative clustering","Latent dirichlet allocation","Topic detection"]} <|eot_id|>
 Here is the Description of a dataset. Description:'FCA.tar.gz (about 3MB)This file contains the FCA implementation as well as the input files for the executionThe dataset can be downloaded from the official RepLab webpage: http://nlp.uned.es/replab2013/' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
FCA.tar.gz (about 3MB)This file contains the FCA implementation as well as the input files for the executionThe dataset can be downloaded from the official RepLab webpage: http://nlp.uned.es/replab2013/
Clustering quality analysis; Formal concept analysis; Hierarchical agglomerative clustering; Latent dirichlet allocation; Topic detection