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 |