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IAB Taxonomy Mapper – Convert Taxonomies Using Ollama

Hacker News

IAB Taxonomy Mapper – Convert Taxonomies Using Ollama

I built a free and open source tool to make working with the IAB content taxonomies less painful. Converts IAB Content Taxonomy 2.0 → 3.0 automatically Runs fully local, no data leaves your machine Multiple methods supported (BM25, TF-IDF, embeddings, LLM re-ranking) Simple demo UI + CLI available pip install iab-taxonomy-mapper Why? Agencies, adtech, and publishers often need to upgrade taxonomies, but mappings aren’t always 1:1. This tool provides ranked candidates and options, saving hours of manual work. GitHub: https://github.com/mixpeek/iab-mapper Demo: https://mxp.co/taxonomy Would love feedback on whether this is useful in your workflow and ideas for what to add next.

Visit productView on Hacker NewsSep 18, 2025
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, using, open · Missing: agents, macos, agent
71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, llama, ide · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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