| Effective hate-speech detection in Twitter data using recurrent neural networks GK Pitsilis, H Ramampiaro, H Langseth Applied Intelligence 48 (12), 4730-4742, 2018 | 141 | 2018 |
| Detecting offensive language in tweets using deep learning GK Pitsilis, H Ramampiaro, H Langseth arXiv preprint arXiv:1801.04433, 2018 | 141 | 2018 |
| GeneTools–application for functional annotation and statistical hypothesis testing V Beisvag, FKR Jünge, H Bergum, L Jølsum, S Lydersen, CC Günther, ... BMC bioinformatics 7 (1), 1-13, 2006 | 112 | 2006 |
| A deep network model for paraphrase detection in short text messages B Agarwal, H Ramampiaro, H Langseth, M Ruocco Information Processing & Management 54 (6), 922-937, 2018 | 104 | 2018 |
| Multi-step classification approaches to cumulative citation recommendation K Balog, H Ramampiaro, N Takhirov, K Nørvåg Proceedings of the 10th conference on open research areas in information …, 2013 | 65 | 2013 |
| Efficient high utility itemset mining using buffered utility-lists QH Duong, P Fournier-Viger, H Ramampiaro, K Nørvåg, TL Dam Applied Intelligence, 19, 2017 | 64 | 2017 |
| Cumulative citation recommendation: Classification vs. ranking K Balog, H Ramampiaro Proceedings of the 36th international ACM SIGIR conference on Research and …, 2013 | 48 | 2013 |
| EfficientPose: Scalable single-person pose estimation D Groos, H Ramampiaro, E Ihlen Applied Intelligence 51, 2518–2533, 2020 | 44 | 2020 |
| Highly efficient pattern mining based on transaction decomposition Y Djenouri, JCW Lin, K Nørvåg, H Ramampiaro 2019 IEEE 35th International Conference on Data Engineering (ICDE), 1646-1649, 2019 | 36 | 2019 |
| Learning to rank for personalised fashion recommender systems via implicit feedback HT Nguyen, T Almenningen, M Havig, H Schistad, A Kofod-Petersen, ... Mining Intelligence and Knowledge Exploration, 51-61, 2014 | 26 | 2014 |
| A scalable algorithm for extraction and clustering of event-related pictures M Ruocco, H Ramampiaro Multimedia Tools and Applications 70 (1), 55-88, 2014 | 24 | 2014 |
| The MOWAHS characterisation framework for mobile work CF Sorensen, AI Wang, HN Le, H Ramampiaro, M Nygard, R Conradi APPLIED INFORMATICS-PROCEEDINGS-, 258-264, 2002 | 20 | 2002 |
| Content-based social recommendation with poisson matrix factorization ES Silva, H Langseth, H Ramampiaro Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 19 | 2017 |
| Requirement Indicators for Mobile Work: The MOWAHS Approach H Ramampiaro, AI Wang, CF Sørensen, HN Le, R Conradi, M Nygård Proceedings of the International Symposia on Applied Informatics, 2003 | 19* | 2003 |
| Towards efficiently mining closed high utility itemsets from incremental databases TL Dam, H Ramampiaro, K Nørvåg, QH Duong Knowledge-Based Systems 165, 13-29, 2019 | 17 | 2019 |
| Extracting news events from microblogs Ø Repp, H Ramampiaro Journal of Statistics and Management Systems 21 (4), 695-723, 2018 | 17 | 2018 |
| Supporting evidence-based software engineering with collaborative information retrieval H Ramampiaro, D Cruzes, R Conradi, M Mendona 6th International Conference on Collaborative Computing: Networking …, 2010 | 17* | 2010 |
| Combining latent semantic indexing and clustering to retrieve and cluster biomedical information: A 2-step approach JR Paulsen, H Ramampiaro NIK-2009 conference, 131-142, 2009 | 16 | 2009 |
| Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles TS Salem, H Langseth, H Ramampiaro 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR volume 124, 2020 | 14 | 2020 |
| Forecasting Intra-Hour Imbalances in Electric Power Systems T Saleh Salem, K Kathuria, H Ramampiaro, H Langseth Association for the Advancement of Artificial Intelligence, 2019 | 14 | 2019 |
Helge LangsethNorwegian University of Science and TechnologyVerified email at ntnu.no
