km#knowledge_modelling/classification/extraction__knowledgemodelling/classification/extraction__knowledge_acquisition__knowledgeacquisition__KA_task__KA  this is "knowledge acquisition" in its restricted sense; in its broader sense, it is equivalent to "knowledge management"
  supertype:  km#knowledge_representation__knowledgerepresentation__representing_knowledge__KR__knowledge_modelling  representing information in a more or less formal way
  part:  km#knowledge_normalization  km#knowledge_inference/reasoning/generation
  part of:  km#collecting_knowledge_for_modelling  km#eliciting_knowledge_from_a_person
  subtype:  km#KA_from_people
  subtype:  km#KA_from_data
     subtype:  km#semi_automatic_KA_from_data__knowledge_discovery__knowledgediscovery__data_mining
        subtype:  km#semi_automatic_KA_from_data_by_classification
           subtype:  km#concept_clustering_from_data
        subtype:  km#knowledge_extraction_from_documents
           subtype:  km#semantic_web_mining
           subtype:  km#knowledge-oriented_NLP
              subtype:  km#CG_extraction_by_NLP
           subtype:  km#ontology_extraction_from_documents
              subtype:  km#terminological_analysis
           subtype:  km#document_structure_analysis_or_discovery
        subtype:  km#knowledge_extraction_from_databases__knowledge_discovery_in_databases__KDD
           subtype:  km#FCA_based_KDD
  subtype:  km#classification
     subtype:  km#conceptual_clustering__concept_clusterization__conceptclusterization  it can be used both for KA and IR, from knowledge or data
        subtype:  km#conceptual_clustering_via_a_generalization_hierarchy
           subtype:  km#conceptual_clustering_via_a_category_generalization_hierarchy
              subtype:  km#FCA_based_conceptual_clustering
                 subtype:  km#FCA_attribute_exploration  FCA technique addressing the problem of a context where the object set is not completely known a priori, or too large to be listed
                 subtype:  km#FCA_concept_exploration  FCA technique addressing the problem of a context where both the object set and the attribute set are not completely known a priori, or too large to be listed
              subtype:  km#type_classification
              subtype:  km#instance_classification__instance_learning  assignement of instances to types of concepts/relations
           subtype:  km#conceptual_clustering_via_a_CG_generalization_hierarchy
        subtype:  km#conceptual_clustering_from_data
           subtype:  km#conceptual_clustering_from_database
           subtype:  km#conceptual_clustering_from_documents
              subtype:  km#conceptual_clustering_from_emails
     subtype:  km#classification_by_semantic_grids

12 statements are about indirect instances of km#knowledge_modelling/classification/extraction: km#graph12_on_article, km#graph13_on_article, km#graph14_on_article, km#graph15_on_article, km#graph18_on_article, km#graph1_on_PhD_thesis, km#graph1_on_book, km#graph21_on_article, km#graph24_on_article, km#graph2_on_PhD_thesis, km#graph25_on_article, km#graph34_on_article
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