Improving the quality of predictions using textual information in online user reviews

@article{Ganu2013ImprovingTQ,
  title={Improving the quality of predictions using textual information in online user reviews},
  author={Gayatree Ganu and Yogesh Kakodkar and Am{\'e}lie Marian},
  journal={Inf. Syst.},
  year={2013},
  volume={38},
  pages={1-15}
}
Online reviews are often accessed by users deciding to buy a product, see a movie, or go to a restaurant. However, most reviews are written in a free-text format, usually with very scant structured metadata information and are therefore difficult for computers to understand, analyze, and aggregate. Users then face the daunting task of accessing and reading a large quantity of reviews to discover potentially useful information. We identified topical and sentiment information from free-form text… CONTINUE READING
Highly Cited
This paper has 73 citations. REVIEW CITATIONS

12 Figures & Tables

Topics

Statistics

01020302012201320142015201620172018
Citations per Year

74 Citations

Semantic Scholar estimates that this publication has 74 citations based on the available data.

See our FAQ for additional information.