We discuss the use of hierarchical transformers for user semantic similarity in the context of analyzing users' behavior and profiling social media users. The objectives of the research include finding the best model for computing semantic user similarity, exploring the use of transformer-based models, and evaluating whether the embeddings reflect the desired similarity concept and can be used for other tasks.
Tag: user profile
Expert finding in social networks and crowdsourcing
Expert selection is an important aspect of many Web applications, e.g., when they aim at matching contents, tasks or advertisement based on user profiles, possibly retrieved from social networks.This was crucial for our current research on crowdsourcing, and therefore we dedicated a specific research line to this aspect. The main idea we developed was to … Continue reading Expert finding in social networks and crowdsourcing