is#information_presentation__informationpresentation
  supertype:  IR_task__information_indexation_or_search__information_retrieval__informationretrieval__IR
  subtype:  knowledge_representation__knowledgerepresentation__representing_knowledge__KR__knowledge_modelling  representing information in a more or less formal way
     subtype:  knowledge_normalization  representing knowledge in a precise, organized and scalable manner; this implies reducing the number of non-automatically comparable ways information is or can be written, and increasing the number of relations between objects (especially common/important relations such as generalization relations, partOf relations and case relations)
        subtype:  use_of_a_normalizing_KRL
        subtype:  re-use_of_a_top_level_or_large_ontology
           subtype:  following_of_an_ontological_principle
              subtype:  following_of_a_principle_of_the_Ontoclean_methodology
        subtype:  following_of_a_category_naming_principle  lexical normalization involves following object naming rules such as "using English singular nouns or nominal expressions" and "avoiding the Intercap style"
           subtype:  following_of_the_InterCap_style_for_naming_categories
           subtype:  following_of_an_underscore_based_style_for_naming_categories
           subtype:  use_of_nouns_or_nominal_forms_for_naming_categories
              subtype:  use_of_singular_nouns_or_nominal_forms_for_naming_categories
        subtype:  following_of_a_phrasing_principle_for_category_annotations
        subtype:  following_of_a_knowledge_organization_principle  Structural and ontological normalization involves following rules such as "when introducing an object into an ontology, relate it to all its already represented direct generalizations, specializations, components and containers", "use subtypeOf relations instead of or in addition to instanceOf relations when both cases are possible", "avoid the use of non binary relations" and "do not represent processes via relations"
           subtype:  use_of_a_graph-oriented-reading_convention
           subtype:  limiting_the_number_of_relation_types
           subtype:  following_of_an_ontological_principle
     subtype:  representing_knowledge_in_a_concise/organized/precise/readable_way
        subtype:  representing_knowledge_in_a_concise_way
        subtype:  representing_knowledge_in_an_organized_way  setting or presenting many relations between categories or statements
           subtype:  increasing_the_number_of_explicit_conceptual_relations_between_conceptual_objects
              subtype:  increasing_the_number_of_explicit_conceptual_relations_between_relation_types
              subtype:  increasing_the_number_of_explicit_conceptual_relations_between_concept_types
              subtype:  increasing_the_number_of_explicit_conceptual_relations_between_objects_from_different_users
        subtype:  representing_knowledge_in_a_readable_way
        subtype:  representing_knowledge_in_a_precise_way  precise or explicit
     subtype:  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"
        subtype:  KA_from_people
        subtype:  KA_from_data
           subtype:  semi_automatic_KA_from_data__knowledge_discovery__knowledgediscovery__data_mining
              subtype:  semi_automatic_KA_from_data_by_classification
                 subtype:  concept_clustering_from_data
              subtype:  knowledge_extraction_from_documents
                 subtype:  semantic_web_mining
                 subtype:  knowledge-oriented_NLP
                    subtype:  CG_extraction_by_NLP
                 subtype:  ontology_extraction_from_documents
                    subtype:  terminological_analysis
                 subtype:  document_structure_analysis_or_discovery
              subtype:  knowledge_extraction_from_databases__knowledge_discovery_in_databases__KDD
                 subtype:  FCA_based_KDD
        subtype:  classification
           subtype:  conceptual_clustering__concept_clusterization__conceptclusterization  it can be used both for KA and IR, from knowledge or data
              subtype:  conceptual_clustering_via_a_generalization_hierarchy
                 subtype:  conceptual_clustering_via_a_category_generalization_hierarchy
                    subtype:  FCA_based_conceptual_clustering
                       subtype:  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:  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:  type_classification
                    subtype:  instance_classification__instance_learning  assignement of instances to types of concepts/relations
                 subtype:  conceptual_clustering_via_a_CG_generalization_hierarchy
              subtype:  conceptual_clustering_from_data
                 subtype:  conceptual_clustering_from_database
                 subtype:  conceptual_clustering_from_documents
                    subtype:  conceptual_clustering_from_emails
           subtype:  classification_by_semantic_grids
     subtype:  language/structure_specific_knowledge_representation
        subtype:  CG_based_KR
     subtype:  methodology_specific_knowledge_representation_or_modelling
        subtype:  task_related_to_the_creation/update_of_the_KB_conceptual_model
           subtype:  creation/update_of_the_KB_conceptual_model
           subtype:  combination_and_instantiation_of_generic_task_models
           subtype:  selection_and_adaptation_of_domain_ontologies

15 statements are about indirect instances of information_presentation: graph1_on_article, graph8_on_article, graph9_on_article, graph12_on_article, graph13_on_article, graph14_on_article, graph15_on_article, graph18_on_article, graph1_on_PhD_thesis, graph1_on_book, graph21_on_article, graph24_on_article, graph2_on_PhD_thesis, graph25_on_article, graph34_on_article click here to display them or click here for a search form or here to add a statement


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