A user on r/MachineLearning is seeking methods to quantify the "distance" between different pieces of online content. They have considered several approaches, including hop count, embedding cosine distance, knowledge graph distance, KL divergence of topic distributions, and information gain. The user acknowledges that each method captures a different aspect of relatedness and is looking for established literature or practical approaches used by practitioners in fields like information retrieval and recommender systems. AI
IMPACT Explores foundational concepts for understanding user navigation and content relationships, potentially impacting recommender systems and search algorithms.
RANK_REASON User-generated discussion on a technical topic, not a primary release or significant industry event.
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