atif-icp

HotelSpamDetection

Project is to determine whether not only a given hotel review on a website is positive or negative, but if the review was genuine or if it was done by spam or a troll/bot. Purpose is to prevent hotels from artificially inflating their own value or to prevent hotels from being spammed by trolls. Algorithm to implement it was a CNN-LSTM network using feature sets from Doc2Vec, POS tags, dependency tags, and TF-IDF. Trained accuracy on validation set was 93.44%.

Pytorch-Tutorial

atif-icp/Pytorch-Tutorial

atif-icp/HotelSpamDetection

Project is to determine whether not only a given hotel review on a website is positive or negative, but if the review was genuine or if it was done by spam or a troll/bot. Purpose is to prevent hotels from artificially inflating their own value or to prevent hotels from being spammed by trolls. Algorithm to implement it was a CNN-LSTM network using feature sets from Doc2Vec, POS tags, dependency tags, and TF-IDF. Trained accuracy on validation set was 93.44%.