{"blocks": [{"key": "f9c9d5be", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "3e6368fc", "text": "Designing a hashtag recommendation system for a social-media platform", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "9db7b967", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "fb0867dd", "text": "What signals or features would you collect to recommend hashtags to users? For users where those features are unavailable or uninformative (e.g., new users), how would you handle recommendations? How would you combine the collected features into a scoring function? How would you determine or learn the weights for each feature?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "374b048f", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "3fb1345f", "text": "Consider engagement history, content similarity, demographics, popularity trends, and weight learning via regression or online learning.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}