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:'Application of Formal Concept Analysis (FCA), an exploratory technique for data analysis and organization. In particular, we propose an extension of FCA-based methods for topic detection applied in the literature by applying the stability concept for the topic selection. The hypothesis is that FCA will enable the better organization of the data and stability the better selection of topics based on this data organization, thus better fulfilling the task requirements by improving the quality and accuracy of the topic detection proces' . 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:'Application of Formal Concept Analysis (FCA), an exploratory technique for data analysis and organization. In particular, we propose an extension of FCA-based methods for topic detection applied in the literature by applying the stability concept for the topic selection. The hypothesis is that FCA will enable the better organization of the data and stability the better selection of topics based on this data organization, thus better fulfilling the task requirements by improving the quality and accuracy of the topic detection proces' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Application of Formal Concept Analysis (FCA), an exploratory technique for data analysis and organization. In particular, we propose an extension of FCA-based methods for topic detection applied in the literature by applying the stability concept for the topic selection. The hypothesis is that FCA will enable the better organization of the data and stability the better selection of topics based on this data organization, thus better fulfilling the task requirements by improving the quality and accuracy of the topic detection proces
Clustering quality analysis; Formal concept analysis; Hierarchical agglomerative clustering; Latent dirichlet allocation; Topic detection