is#information_indexation__informationindexation exclusion: is#information_search supertype: is#IR_task__information_indexation_or_search__information_retrieval__informationretrieval__IR subtype: is#information_structuring increasing the number of relations between objects subtype: is#increasing_the_number_of_relations_between_document_elements subtype: is#document_structuring subtype: is#increasing_the_number_of_relations_between_documents subtype: is#reducing_the_size_of_document_elements subtype: is#information_normalization__informationnormalization subtype: is#data_normalization subtype: is#representing_information_in_a_formal_or_semi_formal_way subtype: km#knowledge_representation__knowledgerepresentation__representing_knowledge__KR__knowledge_modelling representing information in a more or less formal way subtype: km#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: km#use_of_a_normalizing_KRL subtype: km#re-use_of_a_top_level_or_large_ontology subtype: km#following_of_an_ontological_principle subtype: km#following_of_a_principle_of_the_Ontoclean_methodology subtype: km#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: km#following_of_the_InterCap_style_for_naming_categories subtype: km#following_of_an_underscore_based_style_for_naming_categories subtype: km#use_of_nouns_or_nominal_forms_for_naming_categories subtype: km#use_of_singular_nouns_or_nominal_forms_for_naming_categories subtype: km#following_of_a_phrasing_principle_for_category_annotations subtype: km#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: km#use_of_a_graph-oriented-reading_convention subtype: km#limiting_the_number_of_relation_types subtype: km#following_of_an_ontological_principle subtype: km#representing_knowledge_in_a_concise/organized/precise/readable_way subtype: km#representing_knowledge_in_a_concise_way subtype: km#representing_knowledge_in_an_organized_way setting or presenting many relations between categories or statements subtype: km#increasing_the_number_of_explicit_conceptual_relations_between_conceptual_objects subtype: km#increasing_the_number_of_explicit_conceptual_relations_between_relation_types subtype: km#increasing_the_number_of_explicit_conceptual_relations_between_concept_types subtype: km#increasing_the_number_of_explicit_conceptual_relations_between_objects_from_different_users subtype: km#representing_knowledge_in_a_readable_way subtype: km#representing_knowledge_in_a_precise_way precise or explicit subtype: 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" 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 subtype: km#language/structure_specific_knowledge_representation subtype: km#CG_based_KR subtype: km#methodology_specific_knowledge_representation_or_modelling subtype: km#task_related_to_the_creation/update_of_the_KB_conceptual_model subtype: km#creation/update_of_the_KB_conceptual_model subtype: km#combination_and_instantiation_of_generic_task_models subtype: km#selection_and_adaptation_of_domain_ontologies subtype: is#information_precising__informationprecising subtype: is#information_explicitation subtype: is#representing_information_in_a_formal_or_semi_formal_way subtype: is#making_an_informal_sentence_less_contextual subtype: is#information_normalization__informationnormalization subtype: is#data_indexation__informal_object_indexation subtype: is#document_indexation subtype: is#data_indexation_in_database
15 statements are about indirect instances of is#information_indexation: km#graph1_on_article, km#graph8_on_article, km#graph9_on_article, 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 click here to display them or click here for a search form or here to add a statement