Robust temporal graph clustering for group record linkage C Nanayakkara, P Christen, T Ranbaduge Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia …, 2019 | 15 | 2019 |
Evaluation measure for group-based record linkage C Nanayakkara, P Christen, T Ranbaduge, E Garrett The International Journal of Population Data Science (IJPDS) 4 (1), 2019 | 11 | 2019 |
Temporal graph-based clustering for historical record linkage C Nanayakkara, P Christen, T Ranbaduge Proceedings of the 14th International Workshop on Mining and Learning with …, 2018 | 6 | 2018 |
Active Learning Based Similarity Filtering for Efficient and Effective Record Linkage C Nanayakkara, P Christen, T Ranbaduge Pacific-Asia Conference on Knowledge Discovery and Data Mining, 321-333, 2021 | 3 | 2021 |
Unsupervised Graph-based Entity Resolution for Accurate and Efficient Family Pedigree Search. N Kirielle, C Nanayakkara, P Christen, C Dibben, L Williamson, E Garrett, ... EDBT, 2:498-2:510, 2022 | 2 | 2022 |
An Anonymiser Tool for Sensitive Graph Data C Nanayakkara, P Christen, T Ranbaduge EYRE'20 workshop co-located with CIKM 2020 2699 (http://ceur-ws.org/Vol-2699 …, 2020 | 2 | 2020 |
Music emotion recognition with audio and lyrics features C Nanayakkara, H Caldera International Journal of Digital Information and Wireless Communications 6 …, 2016 | 2 | 2016 |
Locality Sensitive Hashing with Temporal and Spatial Constraints for Efficient Population Record Linkage C Nanayakkara, P Christen Proceedings of the 31st ACM International Conference on Information …, 2022 | 1 | 2022 |
Efficient population record linkage with temporal and spatial constraints C Nanayakkara, P Christen International Journal of Population Data Science (IJPDS) 7 (3), 2022 | | 2022 |
Effective Record Linkage Techniques for Complex Population Data C Nanayakkara PQDT-Global, 2022 | | 2022 |
Prediction of Emotion Stimulated by Music CV Nanayakkara | | 2016 |
Identification of Musically Induced Emotion: A Machine Learning Based Approach CV Nanayakkara, HA Caldera Feature Engineering in Hybrid Recommender Systems, 44, 0 | | |