Knowledge Enrichment and Sharing

2016 ◽  
pp. 135-144
Author(s):  
Kristopher Bell
Keyword(s):  
Knowledge Enrichment

Database Knowledge Enrichment Utilizing Trending Topics from Twitter

2020 ◽  
Author(s):  
Costas Vassilakis ◽  
Dimitra Maniataki ◽  
George Lepouras ◽  
Angeliki Antoniou ◽  
Dimitris Spiliotopoulos ◽  
...  
Keyword(s):  
Knowledge Enrichment ◽  
Trending Topics

Procedure Based on Semantic Similarity for Merging Ontologies by Non-Redundant Knowledge Enrichment

2018 ◽  
Vol 14 (2) ◽  
pp. 16-36 ◽  
Author(s):  
Carlos Ramón Rangel ◽  
Junior Altamiranda ◽  
Mariela Cerrada ◽  
Jose Aguilar
Keyword(s):  
Semantic Similarity ◽  
Similarity Measures ◽  
The Other ◽  
Other Hand ◽  
Knowledge Enrichment ◽  
Merging Algorithms

The merging procedures of two ontologies are mostly related to the enrichment of one of the input ontologies, i.e. the knowledge of the aligned concepts from one ontology are copied into the other ontology. As a consequence, the resulting new ontology extends the original knowledge of the base ontology, but the unaligned concepts of the other ontology are not considered in the new extended ontology. On the other hand, there are experts-aided semi-automatic approaches to accomplish the task of including the knowledge that is left out from the resulting merged ontology and debugging the possible concept redundancy. With the aim of facing the posed necessity of including all the knowledge of the ontologies to be merged without redundancy, this article proposes an automatic approach for merging ontologies, which is based on semantic similarity measures and exhaustive searching along of the closest concepts. The authors' approach was compared to other merging algorithms, and good results are obtained in terms of completeness, relationships and properties, without creating redundancy.

scholarly journals Rare disease knowledge enrichment through a data-driven approach

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Feichen Shen ◽  
Yiqing Zhao ◽  
Liwei Wang ◽  
Majid Rastegar Mojarad ◽  
Yanshan Wang ◽  
...  
Keyword(s):  
Rare Disease ◽  
Data Driven ◽  
Disease Knowledge ◽  
Data Driven Approach ◽  
Knowledge Enrichment

scholarly journals Best Paper Selection

2020 ◽  
Vol 29 (01) ◽  
pp. 167-168
Keyword(s):  
Information Systems ◽  
Electronic Health Record ◽  
Rare Disease ◽  
Data Driven ◽  
Health Record ◽  
Quality Changes ◽  
Disease Knowledge ◽  
Data Driven Approach ◽  
Knowledge Enrichment ◽  
Electronic Health

Burek P, Scherf N, Herre H. Ontology patterns for the representation of quality changes of cells in time. J Biomed Semantics 2019;10(1):16 https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-019-0206-4 Denaxas S, Gonzalez-Izquierdo A, Direk K, Fitzpatrick NK Fatemifar G, Banerjee A, Dobson RJB, Howe LJ, Kuan V, Lumbers RT, Pasea L, Patel RS, Shah AD, Hingorani AD, Sudlow C, Hemingway H. UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. J Am Med Inform Assoc 2019;26(12):1545-59 https://academic.oup.com/jamia/article/26/12/1545/5536916 Rector A, Schulz S, Rodrigues J-M, Chute CG, Solbrig H. On beyond Gruber: “Ontologies” in today's biomedical information systems and the limits of OWL. J Biomed Inform: X 2019 Jun 1;2:100002 https://academic.oup.com/jamia/article/26/12/1545/5536916 Shen F, Zhao Y, Wang L, Mojarad MR, Wang Y, Liu S, Liu H. Rare disease knowledge enrichment through a data-driven approach. BMC Med Inform Decis Mak 2019;19(1):32 https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-019-0752-9

Generating Supplier Benefits through Buyer-Enabled Knowledge Enrichment: A Social Capital Perspective

2016 ◽  
Vol 48 (2) ◽  
pp. 248-287 ◽  
Author(s):  
David S. Preston ◽  
Daniel Q. Chen ◽  
Morgan Swink ◽  
Laura Meade
Keyword(s):  
Social Capital ◽  
Knowledge Enrichment ◽  
Social Capital Perspective
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