Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
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The future of organic visibility includes AI citations alongside traditional search rankings. The question isn't whether to optimize for both—it's whether you'll start while competition is light or wait until fighting for AI visibility becomes as challenging as ranking in traditional search is today.
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