Solutions
 
Custom Data Science.
Know your customers and market better than your competitors do.
With custom, small-to-large-scale data analyses
for businesses of every size.

We offer:
  • Consulting. Profit from our internationally renowned, award-winning expertise in Data Science.
  • Data Science Support. We support Data Scientists in the application and development of probabilistic models for Big Data.
  • Advanced Analytics. Gain valuable insights into billing data, usage data or market data with state-of-the-art analyses. Our specialties are text mining and custom probabilistic models.
  • Training. Knowledge ist power. We share our insights in Data Science seminars.
Check our detailed list of offers

Operational area

We offer our services directly and at no extra cost in three regions:
  • Region 1: Hamburg, Kiel
  • Region 2: Cologne / Köln, Düsseldorf, Essen, Koblenz, Bonn
  • Region 3 (Frankfurt Rhine-Main area): Frankfurt, Mainz, Wiesbaden, Rüsselsheim, Ingelheim


News

Koblenz, 27.11.2017
 

Koblenz University Award

Christoph Kling received the 2.500€ Koblenz University Award for his dissertation "Probabilistic Models for Context in Social Media". Read the press release (German)

Koblenz, 26.01.2018

Dissertation Price for Christoph Kling

Christoph Kling received the Disseration Prize of the faculty of computer science at the University of Koblenz-Landau. Dissertations from 10/2016 to 12/2017 were considered. Read the press release (German)

Cologne, 10.04.2018

Paper accepted at WebSci18

The paper "Can We Count on Social Media Metrics? First Insights into the Active Scholarly Use of Social Media" by Maryam Mehrazar and Christoph Kling was accepted at the international ACM Conference on Web Science, Amsterdam. [PDF]
Solutions

Offers

  • Consulting
    • Data Science consulting and support
    • Recruiting: We are experienced in designing and conducting written and oral examinations
  • Advanced Analytics
    • Text Mining with state-of-the-art models (!)
    • Mining of small-to-large billing data, usage data or market data, including context information such as geography, time and authorship
    • Custom probabilistic models
      • Modelling with graphical models
      • Efficient inference (e.g. variational, online, map-reduce-ready)
      • Implementation (Java / Python / Scala + Spark)
      • Deployment (server configuration, application)
    • Interactive data visualisation
    • Web scraping, API querying, merging of datasets
    • Advanced data preparation, e.g. selecting relevant sub-datasets based on latent features
    • Application of standard and state-of-the-art Data Mining / Machine Learning methods
  • Training
    • We have years of experience in teaching Data Science, Machine Learning & Data Mining, and Information Retrieval. Our lectures base on exclusively self-developed Ipython notebooks, visualisations and interactive teaching.
    • Custom seminars covering
      • Statistics (foundations, tests, simple models like regression, Bayesian statistics)
      • Advanced probabilistic models (EM, Gibbs sampling, variational inference, stochastic inference, infinite Gaussian mixture models, topic models, ...)
      • Probabilistic models for Big Data analysis (map-reduce & online inference)
      • Your topic from the area of Data Science, Data Mining, Machine Learning, Information Retrieval
You are interested? Please do not hesitate to get in touch with us!

Telephone: +49 151 236 085 76  

@ Email: dataarascience@c-kesarling.de

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Software

Software

Free Topic Modelling Software

The implementations of my probabilistic topic models I developed at the Institute for Web Science and Technologies (WeST) at the University of Koblenz-Landau and at GESIS, Cologne are free software licensed under GNU GPLv3.

Promoss topic modelling toolbox. This java project contains all my recent topic models I am developing since 2016, including the multi-context topic model described in my dissertation.

Multi-Dirichlet Process Geographical Topic Model (MGTM). My first implementation of a Multi-Dirichlet Process (MDP) topic model, which uses a collapsed Gibbs sampler. This model yields nice topics, but gets stuck in local optima. I still use this model if I want to detect a low number of human-interpretable topics. However, if you want to have perfect results and a faster inference, use the multi-context topic model of the Promoss toolbox.
Contact

About

 
Dr. Christoph Carl Kling

Data Scientist

datatoscience@c-kesarling.de


References

Awards

 
2015  Honorable Mention Award (one out of two) at the AAAI International Conference for Web and Social Media (ICWSM) 2015, Oxford
2017 Nomination for the Dissertation Award of the German Informatics Society (GI)
2017 University Award of Koblenz (2500€) [Press release (German)]
2018 Dissertation Prize 2016/2017 of the Faculty of Computer Science, University of Koblenz-Landau [Press release (German)]

Selected Publications

Christoph Carl Kling. Probabilistic Models for Context in Social Media - Novel Approaches and Inference Schemes. Dissertation, 2016 (pdf)

Christoph Carl Kling, Lisa Posch, Arnim Bleier, Laura Dietz. Topic model tutorial: A basic introduction on latent Dirichlet allocation and extensions for web scientists. Tutorial, International ACM Conference on Web Science (WebSci) 2016 (material)

Christoph Carl Kling, Jerome Kunegis, Heinrich Hartmann, Markus Strohmaier, and Steffen Staab. Voting Behaviour and Power in Online Democracy: A Study of LiquidFeedback in Germany's Pirate Party. AAAI International Conference on Web and Social Media (ICWSM), 2015 (pdf)
Honorable Mention Award, ICWSM 2015

Christoph Carl Kling, Jerome Kunegis, Sergej Sizov, and Steffen Staab. Detecting non-Gaussian geographical topics in tagged photo collections. ACM International Conference on Web and Data Mining (WSDM), 2014 (pdf)

Qualifications

Contact

Contact

If you are interested in our service or consulting solutions or you just have questions - please do not hesitate to get in touch with us. Cost estimates are provided free of charge.

@ Email: datatoscience@c-kesarling.de

Telephone: +49 151 236 085 76  

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Address: Dr. C. C. Kling
Fridolinstr. 44
50825 Köln

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