# Goodreads Books Review Rating Prediction

Reviews are a good way to judge the quality of any product, whether it's books, clothes, technology, or anything else. When you want to buy something online these days, the first thing that comes to mind is the reviews from past buyers and the overall rating the product has received.
Reader feedback, whether positive or negative, five stars or one star, will encourage the product owner to make improvements.
Reader connection and engagement will be encouraged by book reviews, whether they be left on Amazon, Goodreads, or social media. Readers must determine whether or not other readers are enjoying the book.

In this competition you will work with a challenging dataset consisting reviews from the [Goodreads](https://www.goodreads.com/) book review website, and a variety of attributes describing the items. and you have to predict review rating which ranges from 0 to 5.

# Acknowledgements
The dataset of this competition is taken from [UCSD Book Graph](https://sites.google.com/corp/eng.ucsd.edu/ucsdbookgraph/reviews?authuser=0).
If you have any questions or find any bugs regarding these datasets, feel free to contact Mengting Wan (m5wan@ucsd.edu). 

## Citations
please cite the following papers:
* Mengting Wan, Julian McAuley, "[Item Recommendation on Monotonic Behavior Chains](https://www.google.com/url?q=https%3A%2F%2Fgithub.com%2FMengtingWan%2Fmengtingwan.github.io%2Fraw%2Fmaster%2Fpaper%2Frecsys18_mwan.pdf&sa=D&sntz=1&usg=AFQjCNGGcNRW1tSZKPWO0yZsr8mj7MkWuw)", in RecSys'18. [[bibtex](https://www.google.com/url?q=https%3A%2F%2Fdblp.uni-trier.de%2Frec%2Fbibtex%2Fconf%2Frecsys%2FWanM18&sa=D&sntz=1&usg=AFQjCNEy2HDVC1K59JJWybzGgq3MafQcWQ)]
* Mengting Wan, Rishabh Misra, Ndapa Nakashole, Julian McAuley, "[Fine-Grained Spoiler Detection from Large-Scale Review Corpora](https://github.com/MengtingWan/mengtingwan.github.io/raw/master/paper/acl19_mwan.pdf)", in ACL'19. [[bibtex](https://dblp.uni-trier.de/rec/bibtex/conf/acl/WanMNM19)]