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Restaurant Information Extraction (Including Opinion Mining Elements) for the Recommendation System

  • Ekaterina Pronoza
  • Elena Yagunova
  • Svetlana Volskaya
  • Andrey Lyashin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8856)

Abstract

In this paper information extraction method for the restaurant recommendation system is proposed. We aim at the development of an information extraction (IE) system which is intended to be a module of the recommendation system. The IE system is to gather information about different aspects of restaurants from online reviews, structure it and feed the recommendation module with the obtained data. The analyzed frames include service and food quality, cuisine, price level, noise level, etc. In this paper service quality, cuisine type and food quality are considered. As part of corpus preprocessing phase, a method for Russian reviews corpus analysis (as part of information extraction) is proposed. Its importance is shown at the experimental phase, when the application of machine learning techniques to aspects extraction is analyzed. It is shown that the ideas obtained at the corpus preprocessing stage can help to improve machine learning models performance.

Keywords

corpus analysis restaurant reviews information extraction recommendation system machine learning 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ekaterina Pronoza
    • 1
  • Elena Yagunova
    • 1
  • Svetlana Volskaya
    • 1
  • Andrey Lyashin
    • 2
  1. 1.Saint-Petersburg State UniversitySaint-PetersburgRussian Federation
  2. 2.Scicon LtdSaint-PetersburgRussian Federation

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