Technical Implementation and Value of AI Recommender Systems
EasyKol uses a deep learning-based recommendation engine to build a multi-dimensional feature vector space by analyzing the textual content (title, description, tags) posted by webstars through NLP, and combining with computer vision to parse the visual elements (hue, composition, scene). When a user clicks 'Find Similar' on the target Netroots page, the system retrieves K Nearest Neighbors (KNN) accounts in the feature space with industry-leading accuracy of 78%.
This feature effectively solves the problem of 'Netflix search fatigue'. For example, when a beauty brand is looking for bloggers suitable for promoting foundation, the AI can not only recommend review bloggers with the same skin type, but also identify accounts with a fan base that has a female percentage >85% and aged between 18-35 years old, and this kind of fine-matching traditional manual screening takes 3-5 hours/person.
This answer comes from the articleEasyKol: A marketing tool for finding web celebrities (KOLs) and getting their mailboxesThe
