| Gradual forgetting for adaptation to concept drift I Koychev Proceedings of ECAI 2000 Workshop on Current Issues in Spatio-Temporal …, 2000 | 235 | 2000 |
| Adaptation to drifting user’s interests I Koychev, I Schwab Proceedings of ECML2000 Workshop: Machine Learning in New Information Age, 39-46, 2000 | 195 | 2000 |
| In search of credible news M Hardalov, I Koychev, P Nakov Artificial Intelligence: Methodology, Systems, and Applications: 17th …, 2016 | 168 | 2016 |
| Learning to recommend from positive evidence I Schwab, W Pohl, I Koychev Proceedings of the 5th international conference on Intelligent user …, 2000 | 150 | 2000 |
| Fully automated fact checking using external sources G Karadzhov, P Nakov, L Màrquez, A Barrón-Cedeño, I Koychev arXiv preprint arXiv:1710.00341, 2017 | 147 | 2017 |
| A context-aware approach for detecting worth-checking claims in political debates P Gencheva, P Nakov, L Màrquez, A Barrón-Cedeño, I Koychev Proceedings of the International Conference Recent Advances in Natural …, 2017 | 124 | 2017 |
| Fact-checking meets fauxtography: Verifying claims about images D Zlatkova, P Nakov, I Koychev arXiv preprint arXiv:1908.11722, 2019 | 106 | 2019 |
| Learning user interests through positive examples using content analysis and collaborative filtering I Schwab, A Kobsa, I Koychev Internal Memo, GMD, St. Augustin, Germany, 2001 | 79 | 2001 |
| Feature selection and generalisation for retrieval of textual cases N Wiratunga, I Koychev, S Massie European Conference on Case-Based Reasoning, 806-820, 2004 | 78 | 2004 |
| Exposing paid opinion manipulation trolls T Mihaylov, I Koychev, G Georgiev, P Nakov arXiv preprint arXiv:2109.13726, 2021 | 65 | 2021 |
| The dark side of news community forums: Opinion manipulation trolls T Mihaylov, T Mihaylova, P Nakov, L Màrquez, GD Georgiev, IK Koychev Internet Research 28 (5), 1292-1312, 2018 | 63 | 2018 |
| We built a fake news & click-bait filter: what happened next will blow your mind! G Karadzhov, P Gencheva, P Nakov, I Koychev arXiv preprint arXiv:1803.03786, 2018 | 59 | 2018 |
| Learning about users from observation I Schwab, A Kobsa, I Koychev AAAI 2000 Spring Symposium: Adaptive User Interface, 241-247, 2000 | 56 | 2000 |
| Towards automated customer support M Hardalov, I Koychev, P Nakov Artificial Intelligence: Methodology, Systems, and Applications: 18th …, 2018 | 50 | 2018 |
| The Case for Being Average: A Mediocrity Approach to Style Masking and Author Obfuscation: (Best of the Labs Track at CLEF-2017) G Karadzhov, T Mihaylova, Y Kiprov, G Georgiev, I Koychev, P Nakov Experimental IR Meets Multilinguality, Multimodality, and Interaction: 8th …, 2017 | 47 | 2017 |
| Within-document retrieval: A user-centred evaluation of relevance profiling DJ Harper, I Koychev, Y Sun, I Pirie Information Retrieval 7, 265-290, 2004 | 45 | 2004 |
| Tracking drifting concepts by time window optimisation I Koychev, R Lothian International Conference on Innovative Techniques and Applications of …, 2005 | 44 | 2005 |
| EXAMS: A multi-subject high school examinations dataset for cross-lingual and multilingual question answering M Hardalov, T Mihaylov, D Zlatkova, Y Dinkov, I Koychev, P Nakov arXiv preprint arXiv:2011.03080, 2020 | 40 | 2020 |
| Predicting the leading political ideology of YouTube channels using acoustic, textual, and metadata information Y Dinkov, A Ali, I Koychev, P Nakov arXiv preprint arXiv:1910.08948, 2019 | 37 | 2019 |
| Detecting deception in political debates using acoustic and textual features D Kopev, A Ali, I Koychev, P Nakov 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019 | 33 | 2019 |
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