Max Zimmermann

Dr.-Ing. Max Zimmermann

Department of Technical and Business Information Systems

Dr.-Ing. Max Zimmermann

Department of Technical and Business Information Systems


Research

 Research interests:

  • Aspect Based Opinion Mining & Sentiment Analysis
  • Opinion Monitoring
  • Predictive Sentiment Analysis
  • Large Scale Data Analysis
  • Semi-Supervised Stream Classification
  • Stream Mining

Projects:

Datasets

 

Publications

 

2015

Ageing-Based Multinomial Naive Bayes Classifiers Over Opinionated Data Streams. In Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, Carlos Soares, João Gama, and Alípio Jorge (Eds.), Machine Learning and Knowledge Discovery in Databases, (9284):401-416, Springer International Publishing, 2015. URL

Discovering and Monitoring Product Features and the Opinions on them with OPINSTREAM. Neurocomput., (Volume 150)Part A:Pages 1-346, Elsevier Science Publishers B. V., Amsterdam, The Netherlands, The Netherlands, 2015.

Incremental Active Opinion Learning Over a Stream of Opinionated Documents. WISDOM'15 (Workshop on Issues of Sentiment Discovery and Opinion Mining) 2015 at Knowledge Discovery and Data Mining, KDD'15 Workshops 2015, Sydney, Australia, August 10, 2015, 2015.

Extracting opinionated (sub)features from a stream of product reviews using accumulated novelty and internal re-organization. Information Sciences, -, 2015. URL

2014

Discovering and Monitoring Product Features and the Opinions on them with OPINSTREAM. Neurocomput., Elsevier Science Publishers B. V., Amsterdam, The Netherlands, The Netherlands, 2014.

Adaptive Semi Supervised Opinion Classifier With Forgetting Mechanism. Proc. of the 29th Annual ACM Symposium on Applied Computing, ACM, 2014.

A Semi-supervised Self-Adaptive Classifier over Opinionated Streams. Proceedings of the 2014 IEEE 14th International Conference on Data Mining Workshops, IEEE Computer Society, Washington, DC, USA, 2014.

2013

Extracting Opinionated (Sub)Features from a Stream of Product Reviews. In Johannes Fürnkranz, Eyke Hüllermeier, and Tomoyuki Higuchi (Eds.), Discovery Science, (8140):340-355, Springer Berlin Heidelberg, 2013. URL

2012

Discovering Global and Local Bursts in a Stream of News. Proceedings of the 27th Annual ACM Symposium on Applied Computing, 807--812, ACM, New York, NY, USA, 2012. URL

2009

Finding Stops in Error-Prone Trajectories of Moving Objects with Time-Based Clustering. Intelligent Interactive Assistance and Mobile Multimedia Computing, (53):275-286, Springer Berlin Heidelberg, 2009.

 

 

Teaching

Teaching

  • Summer term 2011,2012 & 2013: Exercise class "Data Mining"
  • Winter term 2012: Lecturer "Advanced Topics in Knowledge Management and Discovery (Sentiment/Opinion Mining)"
  • Summer term 2013&2014: Coordinating "Seminar Bachelor"
  • ERASMUS Teachers’ Mobility Program: Short lecture on "Advances in Opinion Stream Mining", Mai 2014 @ University of Thessaloniki, Greece
  • Invited Talk: "Burst detection in streams of news data", September 2011@ University of Thessaloniki, Greece

Advised Theses

Advised Student Team/Software Projects (Software on request)

  • Amazon Review Crawler (2011)
  • Web crawler for job advertisements (2012)
  • Skill predictor on evolving job advertisements (2013)
  • Clustering of Opinionated Documents: A self-organizing map approach (2012)
  • Learning Domain specific Lexicon (2013)
  • Sentiment Visualization (2013)
  • Efficient Unsupervised Discovery of Word Categories (2013)
  • Efficiency of Density Based Hierachical Clustering in Opinion Mining (2014)
  • Learning a polarity lexicon by WordNet Synonyms: A graph clustering approach (2014)

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