Please use this identifier to cite or link to this item:
http://repository.iiitd.edu.in/xmlui/handle/123456789/2152| Title: | KG quality metrics |
| Authors: | Gupta, Aanchal Kumar, Yogender Mukherjee, Manuj (Advisor) Mutharaju, Raghava (Advisor) |
| Keywords: | Knowledge graph (KG) Quality assessment Novel matrices Accuracy Contextual relevance |
| Issue Date: | 26-Nov-2024 |
| Publisher: | IIIT-Delhi |
| Abstract: | In the field of knowledge representation, the construction and maintenance of high quality knowledge graphs (KG’s) play a pivotal role in ensuring the accuracy and reliability of information. This research endeavors to establish a comprehensive framework for assessing the quality of knowledge graphs, introducing novel matrices and metrics tailored to capture the intricacies of knowledge representation. Our approach involves the development of quantifiable measures that evaluate aspects such as completeness, consistency, accuracy, and contextual relevance within a knowledge graph. |
| URI: | http://repository.iiitd.edu.in/xmlui/handle/123456789/2152 |
| Appears in Collections: | Year-2024 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| BTP_REPORT_KG_QUALITY - Yogender Kumar.pdf Restricted Access | 991.13 kB | Adobe PDF | View/Open Request a copy |
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