If you made any changes in Pure these will be visible here soon.

Fingerprint Dive into the research topics where Heiko Angermann is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Taxonomies Engineering & Materials Science
Semantic Web Engineering & Materials Science
Semantics Engineering & Materials Science
Innovation Engineering & Materials Science
Metadata Engineering & Materials Science
Ontology Engineering & Materials Science
Thesauri Engineering & Materials Science
Recommender systems Engineering & Materials Science

Research Output 2017 2018

Background of taxonomic heterogeneity

Angermann, H. & Ramzan, N., 8 Jan 2018, Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories. Springer, p. 15-24 10 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

methodology
inhomogeneity
evaluation

Background taxonomy matching

Angermann, H. & Ramzan, N., 8 Jan 2018, Taxonomy Matching using Background Knowledge: Linked Data, Semantic Web, and Heterogeneous Repositories. Springer, p. 3-13 11 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

Taxonomies
Metadata
Information management
Information systems
Industry

Matching evaluations and datasets

Angermann, H. & Ramzan, N., 8 Jan 2018, Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories. Springer, p. 51-68 18 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

information processing
evaluation
alignment
state of the art
analysis

Matching techniques, algorithms, and systems

Angermann, H. & Ramzan, N., 8 Jan 2018, Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories. Springer, p. 27-50 24 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

Innovation
Thesauri
Taxonomies
Semantic Web

Related areas

Angermann, H. & Ramzan, N., 8 Jan 2018, Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories. Springer, p. 71-83 13 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

Taxonomies
Recommender systems