bookmarks (hide)114
- A Tutorial
- Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
- Argumentation Mining with Deep Learning and Random Forest
- Some of the tools listed below are discussed in detail in the "Seven Layers of Social Media Analytics" book. Applications (no programming skills required) DiscoverText: http://www.screencast.com/t/VKLqaekPz Demographics Pro: http://www.demographicspro.com/ NodeXL: https://nodexl.codeplex.com/ Twitonomy: http://www.twitonomy.com/ RapidMiner: http://docs.rapidminer.com/studio/how-to/cloud-connectivity/twitter.html KPI6: https://www.kpi6.com/ Talend: http://www.datalytyx.com/twitter-sentiment-analysis-using-talend/ KNIME: https://www.knime.org/blog/knime-twitter-nodes Pentaho: http://www.patlaf.com/query-twitter-api-with-pentaho-pdi-kettle/ iScience Maps: http://maps.iscience.deusto.es/ Nexalogy: https://nexalogy.com/ Tools/Scripts/Modules (require programming skills) Twarc: https://github.com/edsu/twarc Twitter for…
- Take free online classes from 120+ top universities and educational organizations. We partner with schools like Stanford, Yale, Princeton, and others to offer courses in dozens of topics, from computer science to teaching and beyond. Whether you are pursuing a passion or looking to advance your career, Coursera provides open, free education for everyone.
- Prof. Dr. Dr. Sergej Sizov - University of Dusseldorf
publications (hide)188
- Data Mining and Knowledge Discovery, 36 (1): 379--413 (January 2022)Funding Information: This research is supported by EDIC project funded by NWO. We thank the EDIC consortium and the ZGT hospital for allowing us to analyse the data from the DIALECT-2 study. We especially thank Niala Den Braber (PhD candidate at Universiteit Twente and researcher internal medicine at ZGT hospital) and prof. dr. Goos Laverman (internist-nephrologist at ZGT hospital) for giving us clinical valuation of our findings. In addition, we thank our colleagues dr. Robert Peharz for giving us useful insights on Markov chains and DBNs and dr. Maryam Tavakol for guiding us towards the MovieLens dataset..
- Data Mining and Knowledge Discovery, 34 (5): 1267--1290 (Sep 1, 2020)
- Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, page 965–974. New York, NY, USA, Association for Computing Machinery, (2016)
- MIS Q., 38 (1): 73--100 (March 2014)
- Nature Methods, 16 (6): 505--507 (2019)
- Information Sciences, (2018)
- (2003)
- Big Data, 1 (1): 51--59 (March 2013)
- ACM Trans. Internet Technol., 16 (2): 10:1--10:25 (March 2016)
- Web Mining: From Web to Semantic Web, Springer, (2004)
- Web Mining: From Web to Semantic Web, Springer, (2004)
- Semantic Web, 8 (5): 623--624 (April 2017)2017 IOS Press and the authors. This is an author produced version of a paper subsequently published in Semantic Web. Uploaded in accordance with the publisher's self-archiving policy..
- Semantic Web, 8 (5): 623--624 (April 2017)2017 IOS Press and the authors. This is an author produced version of a paper subsequently published in Semantic Web. Uploaded in accordance with the publisher's self-archiving policy..
- IUI '00: Proceedings of the 5th International Conference on Intelligent User Interfaces, page 106--112. New York, NY, USA, ACM Press, (2000)
- CRC Press, Boca Raton, Fl., (2010)
- Morgan Kaufmann, Amsterdam; London, (2017)
- EMNLP, page 1822-1827. ACL, (2014)
- Mining, Modeling and Recommending 'Things' in Social Media, volume 8940 of Lecture Notes in Computer Science, (2015)
- Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases., Heidelberg, Germany, Springer Verlag, (2012)
- DMNLP@PKDD/ECML, volume 1646 of CEUR Workshop Proceedings, page 9-16. CEUR-WS.org, (2016)
