My objective is to derive product descriptions from online reviews.
Product descriptions are typically more objective than reviews, since reviews are the buyer’s impression of a product.
However, many products have too many reviews that make it hard to interpret them all.
Therefore, shoppers usually only read a few of them and may miss relevant information.
To address this issue, we have come up with the idea to collate accurate review sentences into item descriptions or features.
Some of the reviews are already descriptive enough to be used as features.
To generate the features automatically, I employed semantic similarity to extract sentences from user reviews and remove sentences which do not provide much information or have similar content.
My goal is to select sentences from each review which accurately depict the product without any adjustments. These are the resulting features which form the final product review.