Leveraging Clustering Algorithms on Connected Components for Entity Resolution
| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | Karnstedt-Hulpus, I.R. | |
| dc.contributor.author | Hoogmoed, Frank | |
| dc.date.accessioned | 2023-07-07T00:01:20Z | |
| dc.date.available | 2023-07-07T00:01:20Z | |
| dc.date.issued | 2023 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/44129 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | A comparative evaluation of multiple clustering algorithms on the task of Entity resolution. Furthermore, a method for selecting the best clustering algorithm on a per connected component basis is proposed to enhance the final clustering result by leveraging multiple different clustering algorithms. | |
| dc.title | Leveraging Clustering Algorithms on Connected Components for Entity Resolution | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Computing Science | |
| dc.thesis.id | 18428 |
