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Always Recommend Talent #45
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View | Contribution | Count | Reward |
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Issue | Specification | 1 | 22.74 |
Review | Comment | 4 | 5.658 |
Conversation Incentives
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We need to calibrate the relevance thresholds for issue dedupe a… | 3.79content: content: p: score: 0 elementCount: 4 result: 0 regex: wordCount: 72 wordValue: 0.1 result: 3.79 | 1 | 2 | 22.74 |
QA seems fine | 0.25content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 3 wordValue: 0.1 result: 0.25 | 0.2 | 2 | 0.1 |
QA? | 0.1content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 1 wordValue: 0.1 result: 0.1 | 0.1 | 2 | 0.02 |
Why does it only work after you close it? It's supposed to be im… | 1.38content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 22 wordValue: 0.1 result: 1.38 | 0.8 | 2 | 2.208 |
Sorry but this doesn't make any sense to me. It doesn't matter w… | 1.85content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 31 wordValue: 0.1 result: 1.85 | 0.9 | 2 | 3.33 |
@sshivaditya2019 the deadline is at Wed, Dec 11, 1:48 AM UTC |
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View | Contribution | Count | Reward |
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Issue | Task | 1 | 100 |
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Resolves #451. The DB gets populated by handling issue complet… | 1content: content: p: score: 0 elementCount: 3 ol: score: 0 elementCount: 1 li: score: 0.5 elementCount: 2 result: 1 regex: wordCount: 23 wordValue: 0 result: 0 | 0.9 | 2 | 0 |
QA:Without alwaysRecommend:[More than threshold](https://git… | 20content: content: p: score: 0 elementCount: 7 a: score: 5 elementCount: 4 result: 20 regex: wordCount: 23 wordValue: 0 result: 0 | 0.8 | 2 | 0 |
In the QA examples, all of them had similarity more than 90%. Ot… | 5content: content: p: score: 0 elementCount: 2 a: score: 5 elementCount: 1 result: 5 regex: wordCount: 22 wordValue: 0 result: 0 | 0.7 | 2 | 0 |
Yeah it does always recommend talent based on title, when edited… | 0content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 40 wordValue: 0 result: 0 | 0.8 | 2 | 0 |
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Contributions Overview
View | Contribution | Count | Reward |
---|---|---|---|
Issue | Specification | 1 | 7.58 |
Review | Comment | 4 | 5.588 |
Conversation Incentives
Comment | Formatting | Relevance | Priority | Reward |
---|---|---|---|---|
We need to calibrate the relevance thresholds for issue dedupe a… | 3.79content: content: p: score: 0 elementCount: 4 result: 0 regex: wordCount: 72 wordValue: 0.1 result: 3.79 | 1 | 2 | 7.58 |
QA seems fine | 0.25content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 3 wordValue: 0.1 result: 0.25 | 0.1 | 2 | 0.05 |
QA? | 0.1content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 1 wordValue: 0.1 result: 0.1 | 0 | 2 | 0 |
Why does it only work after you close it? It's supposed to be im… | 1.38content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 22 wordValue: 0.1 result: 1.38 | 0.8 | 2 | 2.208 |
Sorry but this doesn't make any sense to me. It doesn't matter w… | 1.85content: content: p: score: 0 elementCount: 1 result: 0 regex: wordCount: 31 wordValue: 0.1 result: 1.85 | 0.9 | 2 | 3.33 |
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We need to calibrate the relevance thresholds for issue dedupe and the talent recommendation because i havent seen them work since we first deployed the plugins.
I think we should always suggest at least one contributor (three default, in order of relevance) so we can test and see how accurate it is
This should be a config option to always recommend
If its 0 or missing we can do as we are.
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