Web3Recommend #160
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Web3Recommend #160
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…TODO. Extracted Node to Node network into a different network from trust network. Still need to integrate both networks later. This separation seems cleaner but can be revisisted.
…, seems redundant, we can always use compact representation
…t based modifications
… for all ranking algos
…/songs can be correctly hashed
…nd create new tests
rmadhwal
commented
Jul 7, 2023
| @@ -139,7 +139,6 @@ class FOCCommunity( | |||
| val torrentHash = payload.message.substringAfter("magnet:?xt=urn:btih:") | |||
| .substringBefore("&dn=") | |||
| if (torrentMessagesList.none { | |||
| it.second | |||
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this looked like a typo in a previous PR, I've removed it, wasn't sure if it was appropriate to do it as a part of this PR - will remove it if you'd rather I commit it separately
AI-Bitcoin-Bittorrent-P2P app😲 Solid work 🎊 🎊 🎊 🎊 🎊 This PR adds monte-carlo based basic machine learning for content discovery and recommendation. With this existing Bitcoin Taproot based DAO work and Bittorrent audio streaming we have a full buzzword bingo. All without profit and without irony we aim to erode Big Tech coming decades(s). |
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Adds recommendation tab to MusicDAO and Web3Recommend code as part of work in this issue
The code in the recommender folder is intended as standalone so I've avoided extracting constants. I'm storing serialized graphs locally in txt files, I wasn't sure if that's anticonventional, if it is let me know and I'll look into using a db for it instead.
I'm not very confident about the code on the MusicDAO side since it's hard to test the UI there without a proper UI testing framework that the project lacks. Maybe someone can look at integrating Espresso in a future integration.
Let me know if there are any concerns with the code.
@synctext