Towards Making Sense of Online Reviews Based on Statement Extraction
Michael Rist, Ahmet Aker, Norbert Fuhr · 2018
Product reviews are valuable resource for information seeking and decision making purposes.Products such as smart phone are discussed based on their aspects e.g.battery life, screen quality, etc. Knowing user statements about aspects is relevant as it will guide other users in their buying process.In this paper, we automatically extract user statements about aspects for a given product.Our extraction method is based on dependency parse information of individual reviews.The parse information is used to learn patterns and use them to determine the user statements for a given aspect.Our results show that our methods are able to extract potentially useful statements for given aspects.