Showing posts from LDA tag
Are words enough?: a study on text-based representations and retrieval models for linking pins to online shops
User-generated content offers opportunities to learn about people’s interests and hobbies. We can leverage this infor- mation to help users find interesting shops and businesses find interested users. However this content is highly noisy and unstructured as posted on social media sites and blogs. In this work we evaluate different textual representations and retrieval models that aim to make sense of social media data for retail applications. Our task is to link the text of pins (from …