Enhancing text classification to improve information filtering C Lanquillon Otto-von-Guericke-Universität Magdeburg, Universitätsbibliothek, 2001 | 68 | 2001 |
Advanced analytics mit big data C Lanquillon, H Mallow Praxishandbuch Big Data, 55-89, 2015 | 64 | 2015 |
Information filtering in changing domains C Lanquillon Proceedings of the international joint conference on artificial intelligence …, 1999 | 57 | 1999 |
Adaptive information filtering: Detecting changes in text streams C Lanquillon, I Renz Proceedings of the eighth international conference on information and …, 1999 | 38 | 1999 |
Blockchain und maschinelles Lernen S Schacht, C Lanquillon Wie das maschinelle Lernen und die Distributed-Ledger-Technologie …, 2019 | 32 | 2019 |
Structural change and classification C Taylor, G Nakhaeizadeh, C Lanquillon Workshop Notes on Dynamically Changing Domains: Theory Revision and Context …, 1997 | 27 | 1997 |
Partially supervised text classification: Combining labeled and unlabeled documents using an EM-like scheme C Lanquillon Machine Learning: ECML 2000: 11th European Conference on Machine Learning …, 2000 | 22 | 2000 |
Introducing DASC-PM: a data science process model M Schulz, U Neuhaus, J Kaufmann, D Badura, S Kuehnel, W Badwitz, ... | 21 | 2020 |
Grundzüge des maschinellen Lernens C Lanquillon Blockchain und maschinelles Lernen: Wie das maschinelle Lernen und die …, 2019 | 19 | 2019 |
Wirtschaft J Dorschel, W Dorschel, U Föhl, W van Geenen, D Hertweck, M Kinitzki, ... Praxishandbuch Big Data: Wirtschaft–Recht–Technik, 15-166, 2015 | 17 | 2015 |
Evaluating Usefulness for Dynamic Classification. G Nakhaeizadeh, CC Taylor, C Lanquillon KDD 1, 87, 1998 | 17 | 1998 |
Mining frequent temporal patterns in interval sequences S Kempe, J Hipp, C Lanquillon, R Kruse International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2008 | 14 | 2008 |
DASC-PM v1. 1-Ein Vorgehensmodell für Data-Science-Projekte M Schulz, U Neuhaus, J Kaufmann, S Kühnel, EM Alekozai, H Rohde, ... Universitäts-und Landesbibliothek Sachsen-Anhalt, 2022 | 13 | 2022 |
Rule cubes for causal investigations A Blumenstock, F Schweiggert, M Müller, C Lanquillon Knowledge and Information Systems 18, 109-132, 2009 | 13 | 2009 |
Learning from labeled and unlabeled documents: A comparative study on semi-supervised text classification C Lanquillon Principles of Data Mining and Knowledge Discovery: 4th European Conference …, 2000 | 13 | 2000 |
Towards energy-efficient deep learning: An overview of energy-efficient approaches along the deep learning lifecycle V Mehlin, S Schacht, C Lanquillon arXiv preprint arXiv:2303.01980, 2023 | 12 | 2023 |
Dynamic neural classification C Lanquillon Master thesis, Fachbereich Informatik, Universität Braunschweig, Germany, 1997 | 11 | 1997 |
Interactivity Closes the Gap-Lessons Learned in an Automotive Industry Application A Blumenstock, M Mueller, C Lanquillon, S Kempe, J Hipp, R Wirth Data Mining for Business Applications, 17-34, 2010 | 10 | 2010 |
Technik G Fels, C Lanquillon, H Mallow, F Schinkel, C Schulmeyer, C Lanquillon, ... Praxishandbuch Big Data: Wirtschaft–Recht–Technik, 255-330, 2015 | 9 | 2015 |
Dynamic aspects in neural classification C Lanquillon Intelligent Systems in Accounting, Finance & Management 8 (4), 281-296, 1999 | 9 | 1999 |