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Recommender System Based on Unstructured Data

  • Katarzyna TarnowskaEmail author
  • Zbigniew W. Ras
  • Lynn Daniel
Chapter
  • 414 Downloads
Part of the Studies in Big Data book series (SBD, volume 55)

Abstract

As the time constraints for completing customer satisfaction surveys are becoming tighter, there emerges a need for developing a new format of surveying customers. The idea is to limit the number of score benchmark questions, and let customers express their opinions in a free format. As a result the collected data will mainly contain open-ended text comments. This chapter presents a strategy to modify the existing recommender system built based on both numerical (structured) and text data (unstructured) to work on unstructured data only to make it work with the new survey format.

References

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    F. A. Nielsen. A new anew: Evaluation of a word list for sentiment analysis in microblogs. CoRR, arXiv:1103.2903, 2011.
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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Katarzyna Tarnowska
    • 1
    Email author
  • Zbigniew W. Ras
    • 2
    • 3
  • Lynn Daniel
    • 4
  1. 1.Department of Computer ScienceSan Jose State UniversitySan JoseUSA
  2. 2.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA
  3. 3.Polish-Japanese Academy of Information TechnologyWarsawPoland
  4. 4.The Daniel GroupCharlotteUSA

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