zhenghaoz

6 ms·

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Show HN: Gorse 0.5 – Open-source recommender system with visual workflow editor(github.com)
2 points by zhenghaoz 8mo ago|0 comments
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Build Recommender System with LLM Ranker via Drag-and-Drop(gorse.io)
3 points by zhenghaoz 8mo ago|0 comments
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Show HN: Building a Recommender System for GitHub Repositories(gorse.io)
1 points by zhenghaoz 9mo ago|0 comments
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Show HN: FlashLite – Flash emulator for Android based on Ruffle(flashlite.games)
1 points by zhenghaoz 3y ago|0 comments
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by zhenghaoz 4y ago
Thanks, @gnabgib. Your comment is very insightful and reminds me of my mentor correcting my academic paper. The post introduces the basic idea of using AVX512 in Go by writing C codes. There are mistakes and many details are omitted. A comp
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by zhenghaoz 4y ago
It is a pity that CGO isn't in the final benchmark. >_<
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by zhenghaoz 4y ago
For someone experts assembly, avo is a better tool to write assembly in hand.
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by zhenghaoz 4y ago
I am the author and I am really regret about this title. I think a better title should be "How to Use AVX512 in Golang via the C Compiler" :O
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Show HN: GitRec – A recommender system for GitHub repositories(github.com)
1 points by zhenghaoz 4y ago|0 comments
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by zhenghaoz 5y ago
I think NLP technology should be used for your project :) I plan to integrate Gorse with NLP, but it might take years to implement it.
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by zhenghaoz 5y ago
Thanks for your insight. In the recommendation scenario that freshness is important, real-time recommendation is more in demand.
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by zhenghaoz 5y ago
To be honest, popular items have more chance to be recommended, and it is hard to avoid. Popular items have higher probability to be liked. In addition, popular items have more data collected, it helps to locate potential users.
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by zhenghaoz 5y ago
The reason to use real time recommendations is there are contextual informations. However, Gorse doesn't use contextual informations, it doesn't handle real time recommendations yet.
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by zhenghaoz 5y ago
Once I collect context aware dataset, context aware recommenders could be implemented :)
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by zhenghaoz 5y ago
Thanks. I will take a look at it :)
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by zhenghaoz 5y ago
Graph databases are good at locating related items/users, which is useful for recommender systems :)
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by zhenghaoz 5y ago
I will try it :)
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by zhenghaoz 5y ago
I list papers here: https://docs.gorse.io/ch01-02-recommend.html#online-evaluati... I will introduce algorithms briefly in documents in the future :)
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by zhenghaoz 5y ago
Yeah, I know "Gource", another cool project. :D
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by zhenghaoz 5y ago
Good idea! But before that, we have to take a look at GDPR :D
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by zhenghaoz 5y ago
The problem is how to utilize these signals. The annoying thing is we can't solve these issues if we are not in this situation. So, feedbacks from Gorse users are important.
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by zhenghaoz 5y ago
Your consideration is absolutely right. The abstractions in Gorse do lose lots of informations. Prior knowedges, contextual informations is important to further improve recommender systems.
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by zhenghaoz 5y ago
Thanks for your advice
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by zhenghaoz 5y ago
There are no explicit negative feedback yet. When a item is seen by a user, the read event is recorded. If this user likes this item, the positive feedback is recorded. It seems a natural way to track user's preference. I will try to a
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Show HN: Gorse – An Out-of-the-box open-source Recommender System(gorse.io)
212 points by zhenghaoz 5y ago|41 comments
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Build a Steam Recommender System with Flask and Gorse(zhenghaoz.github.io)
1 points by zhenghaoz 7y ago|0 comments
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Gorse: A Recommender System Package Based on Collaborative Filtering for Go(github.com)
2 points by zhenghaoz 8y ago|0 comments