Survey on aspect-level sentiment analysis K Schouten, F Frasincar IEEE transactions on knowledge and data engineering 28 (3), 813-830, 2015 | 918 | 2015 |
Supervised and unsupervised aspect category detection for sentiment analysis with co-occurrence data K Schouten, O Van Der Weijde, F Frasincar, R Dekker IEEE transactions on cybernetics 48 (4), 1263-1275, 2017 | 171 | 2017 |
Semantics-based information extraction for detecting economic events A Hogenboom, F Hogenboom, F Frasincar, K Schouten, O Van Der Meer Multimedia Tools and Applications 64, 27-52, 2013 | 85 | 2013 |
Finding implicit features in consumer reviews for sentiment analysis K Schouten, F Frasincar Web Engineering: 14th International Conference, ICWE 2014, Toulouse, France …, 2014 | 59 | 2014 |
A semantic web-based approach for personalizing news K Schouten, P Ruijgrok, J Borsje, F Frasincar, L Levering, F Hogenboom Proceedings of the 2010 ACM symposium on applied computing, 854-861, 2010 | 51 | 2010 |
Ontology-enhanced aspect-based sentiment analysis K Schouten, F Frasincar, F de Jong Web Engineering: 17th International Conference, ICWE 2017, Rome, Italy, June …, 2017 | 48 | 2017 |
Framing a conflict! How media report on earthquake risks caused by gas drilling: A longitudinal analysis using machine learning techniques of media reporting on gas drilling … AE Opperhuizen, K Schouten, EH Klijn Journalism Studies 20 (5), 714-734, 2019 | 46 | 2019 |
Ontology-driven sentiment analysis of product and service aspects K Schouten, F Frasincar The Semantic Web: 15th International Conference, ESWC 2018, Heraklion, Crete …, 2018 | 37 | 2018 |
Commit-p1wp3: A co-occurrence based approach to aspect-level sentiment analysis K Schouten, F Frasincar, F De Jong Proceedings of the 8th International Workshop on Semantic Evaluation …, 2014 | 31 | 2014 |
Aggregated Aspect-based Sentiment Analysis with Ontology Features S de Kok, L Punt, R van den Puttelaar, K Ranta, K Schouten, F Frasincar Progress in Artificial Intelligence 7 (4), 295-306, 2018 | 30 | 2018 |
SOBA: Semi-automated ontology builder for aspect-based sentiment analysis L Zhuang, K Schouten, F Frasincar Journal of Web Semantics 60, 100544, 2020 | 29 | 2020 |
Aspect-based sentiment analysis on the web using rhetorical structure theory R Hoogervorst, E Essink, W Jansen, M Van Den Helder, K Schouten, ... Web Engineering: 16th International Conference, ICWE 2016, Lugano …, 2016 | 28 | 2016 |
An information gain-driven feature study for aspect-based sentiment analysis K Schouten, F Frasincar, R Dekker Natural Language Processing and Information Systems: 21st International …, 2016 | 23 | 2016 |
Review-Level Aspect-Based Sentiment Analysis Using an Ontology S de Kok, L Punt, R van den Puttelaar, K Ranta, K Schouten, F Frasincar | 22* | 2018 |
Detection of multiple implicit features per sentence in consumer review data N Dosoula, R Griep, R den Ridder, R Slangen, K Schouten, F Frasincar Databases and Information Systems: 12th International Baltic Conference, DB …, 2016 | 16 | 2016 |
How do media, political and regulatory agendas influence one another in high risk policy issues? AE Opperhuizen, EH Klijn, K Schouten Policy & Politics 48 (3), 461-483, 2020 | 13 | 2020 |
Heracles: A framework for developing and evaluating text mining algorithms K Schouten, F Frasincar, R Dekker, M Riezebos Expert Systems with Applications 127, 68-84, 2019 | 13 | 2019 |
Sentiment analysis of multiple implicit features per sentence in consumer review data N Dosoula, R Griep, R Den Ridder, R Slangen, R Van Luijk, K Schouten, ... Databases and information systems IX, 241-254, 2016 | 13 | 2016 |
The benefit of concept-based features for sentiment analysis K Schouten, F Frasincar Semantic Web Evaluation Challenges, 223-233, 2015 | 13 | 2015 |
Semantics-driven implicit aspect detection in consumer reviews K Schouten, N De Boer, T Lam, M Van Leeuwen, R Van Luijk, F Frasincar Proceedings of the 24th International Conference on World Wide Web, 109-110, 2015 | 13 | 2015 |