Subjective Search Intent Predictions using Customer Reviews

Query intent prediction is a component of information retrieval which improves result relevance through an understanding of latent user intents in addition to explicit query keywords. We target context-of-use intents, such as the activity for which a product is used and the target audience for a product, which are subjective and not usually indexed as product attributes in the catalog. We describe a method to predict latent query intents: we extract intents from product reviews on amazon.com and, using behavioral purchase signals that associate queries with the reviewed products, train query classifiers that label queries with the intents extracted from reviews. For example, we predict the activity "running" for the query "adidas mens pants." We show that our method can predict latent intents not indexed directly in the product catalog.