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Knowledge atlas (VI): Knowledge Fusion

2022-01-26 23:58:25 Hz in nuggets 75963

What is knowledge fusion

 That is to merge two knowledge maps ( noumenon / Entity ).
 The basic problem is to study how to integrate the description information about the same entity or concept from multiple sources .
 What needs to be confirmed is :
    -  Equivalent instance 
    -  Equivalence class / Subclass 
    -  Equivalent attribute / Sub properties 
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 An example is shown in the figure above , The circles of different colors in the figure represent different sources of knowledge map ,
 Among them in dbpedia.org In the source Rome  and geoname.org From roma It's the same entity , Through two sameAs link .
 The entity alignment between different knowledge maps is KG The main work of integration .

 In addition to solid alignment , There is also knowledge fusion at the conceptual level 、 Cross language knowledge integration, etc .

 It's worth mentioning here , In different literature , Knowledge fusion has different names , Such as body alignment 、 Ontology matching 、Record Linkage、Entity Resolution、 Entity alignment, etc , But their essential work is the same .

 The main technical challenges of knowledge fusion are two points :
    The challenge of data quality : Such as vague naming , Data input error 、 Data loss 、 Inconsistent data format 、 Abbreviations, etc .
                 And how to identify 2 Two entities are the same entity , Only the same entity can be fused .
                
    The challenge of data scale : Large amount of data ( Parallel computing )、 Variety of data 、 No longer match just by name 、 Multiple relationships 、 More links, etc .
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Come back , relation , Fusion and optimization

 Come back : It refers to whether the entity to be included is the same entity .
      Literally , Many belong to one . If several entities to be included are the same entity , First, attribute these entities to be included to one entity .


 relation : Whether the entity to be included and the entity in the core set are the same entity .
 Fusion and optimization : It is the preference of entity attributes .
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