this post was submitted on 05 Jul 2024
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Game #144
Shortest path: 3 (Avg. 5.5)
Total words: 4 (Avg. 11.8)
🟦πŸŸͺπŸŸ₯ | πŸ”₯ 2

https://linxicon.com
#Linxicon

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[–] jol@discuss.tchncs.de 4 points 2 months ago* (last edited 2 months ago) (1 children)

This must be the most frustrating game like these. I don't get the intuition of why some words are decided distance. I guess it takes into account all possible meanings.

Edit: in the end I was able to get the perfect score after several tries.

[–] themoonisacheese@sh.itjust.works 4 points 2 months ago (1 children)

This type of game is based off a dataset that came out a few years ago, that was originally built to train AI. It's built by analysing all text fed to it (pretty much all of Google book and a very large part of the internet) and whether a word is close or not depends on how frequently the words appear near each other.

[–] MicrowavedTea@infosec.pub 3 points 2 months ago (1 children)

how frequently the words appear near each other

That's what I thought for yesterday's puzzle and tried "final" and "version" but apparently there was no connection between them. I guess if you keep playing you'll start learning the dataset too.

[–] jol@discuss.tchncs.de 3 points 2 months ago (1 children)

One thing I misunderstood is that it's not about how close they are semantically, but in meaning. It's subtle.

[–] perishthethought@lemm.ee 3 points 2 months ago (1 children)

I just played for the first time and got:

Game #144
Shortest path: 3 (Avg. 3)
Total words: 3 (Avg. 3)
🟦πŸŸͺπŸŸ₯ | πŸ”₯ 1

I must have just got lucky with the word I chose: >!food!<

[–] lemonmelon@lemmy.world 2 points 2 months ago

Interestingly, I chose the same word that you did. But the direct connection to "living" seems to be a stretch.

Game #144 Shortest path: 4 (Avg. 4) Total words: 4 (Avg. 4) 🟦🟦πŸŸ₯πŸŸ₯ | πŸ”₯ 1

https://linxicon.com #Linxicon

[–] MicrowavedTea@infosec.pub 2 points 2 months ago
Game #144
Shortest path: 3 (Avg. 4)
Total words: 3 (Avg. 6)
🟦πŸŸͺπŸŸ₯ | πŸ”₯ 2

https://linxicon.com
#Linxicon

That was unexpected

[–] inlandempire@jlai.lu 2 points 2 months ago
Game #144
Shortest path: 3 (Avg. 5)
Total words: 3 (Avg. 6)
🟦πŸŸͺπŸŸ₯ | πŸ”₯ 2

https://linxicon.com
#Linxicon
[–] berryjam@lemmy.world 2 points 2 months ago* (last edited 2 months ago)
Game #144
Shortest path: 5 (Avg. 5)
Total words: 6 (Avg. 14.8)
🟦🟦πŸŸͺπŸŸ₯πŸŸ₯ | πŸ”₯ 1

https://linxicon.com
#Linxicon
[–] JoMiran@lemmy.ml 2 points 2 months ago (1 children)

Game #144
Shortest path: 7 (Avg. 7)
Total words: 12 (Avg. 12)
🟦🟦🟦πŸŸͺπŸŸ₯πŸŸ₯πŸŸ₯ | πŸ”₯ 1

I am not sure how it determines links or not because I gave it many linked words and it did not agree.

[–] Emotional_Series7814@kbin.melroy.org 2 points 2 months ago (1 children)

I get frustrated by this too. Figured I'd post a new game but if people don't like it I can stop. I like it well enough to put up with some words that really should be linked not being linked, and unexpected words linking, but I can see why not everyone would.

3. How does Linxicon determine how similar words are to each other? Behind the scenes, words are entered into a machine learning model that returns a score which indicates how similar words are to each other. If you want to learn more about the model used, click here to the documentation on SentenceTransformers.

source: https://linxicon.com/faq

[–] JoMiran@lemmy.ml 2 points 2 months ago

Yeah, it quickly turns into a game of "what does the LLM want", instead of the intended word relationship.

[–] lemonmelon@lemmy.world 2 points 2 months ago (1 children)

Game #144
Shortest path: 3 (Avg. 4.5)
Total words: 3 (Avg. 6.5)
🟦πŸŸͺπŸŸ₯ | πŸ”₯ 2

I'm still not sold on this one; it's interesting enougn but it seems incredibly subjective. I don't believe my word should have connected to "living", and there was a link yesterday that wouldn't form that I'm convinced should have.

I feel the same way about the links.

3. How does Linxicon determine how similar words are to each other? Behind the scenes, words are entered into a machine learning model that returns a score which indicates how similar words are to each other. If you want to learn more about the model used, click here to the documentation on SentenceTransformers.

source: https://linxicon.com/faq