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improve trust

This commit is contained in:
keyan 2022-06-27 15:49:52 -05:00
parent d86bf302ee
commit 9d3c52ed00
6 changed files with 101 additions and 9 deletions
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1
.gitignore vendored
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@ -19,6 +19,7 @@
.DS_Store
*.pem
db.sql
test.sql
# debug
npm-debug.log*

2
api/resolvers/notifications.js
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@ -110,7 +110,7 @@ export default {
JOIN "ItemAct" ON "ItemAct"."itemId" = "Item".id
WHERE "ItemAct"."userId" <> $1
AND "ItemAct".created_at <= $2
AND "ItemAct".act <> 'BOOST'
AND "ItemAct".act in ('VOTE', 'TIP')
AND "Item"."userId" = $1
GROUP BY "Item".id
ORDER BY "sortTime" DESC

25
prisma/migrations/20220630170204_upvote_trust/migration.sql Normal file
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@ -0,0 +1,25 @@
-- AlterTable
ALTER TABLE "users" ADD COLUMN "upvoteTrust" DOUBLE PRECISION NOT NULL DEFAULT 0;
CREATE OR REPLACE FUNCTION confidence(successes FLOAT, trials FLOAT, z FLOAT)
RETURNS FLOAT
LANGUAGE plpgsql
AS $$
DECLARE
p FLOAT;
lhand FLOAT;
rhand FLOAT;
under FLOAT;
BEGIN
IF trials = 0 THEN
RETURN 0;
END IF;
p := successes / trials;
lhand := p + 1 / (2 * trials) * z * z;
rhand := z * sqrt(p * (1 - p) / trials + z * z / (4 * trials * trials));
under := 1 + 1 / trials * z * z;
RETURN (lhand - rhand) / under;
END;
$$;

1
prisma/schema.prisma
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@ -38,6 +38,7 @@ model User {
tipDefault Int @default(10)
pubkey String? @unique
trust Float @default(0)
upvoteTrust Float @default(0)
lastSeenAt DateTime?
lastCheckedJobs DateTime?
photoId Int?

25
worker/confidence.js Normal file
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@ -0,0 +1,25 @@
// https://en.wikipedia.org/wiki/Normal_distribution#Quantile_function
// const z = 1.281551565545 // 80% confidence
// const z = 1.644853626951 // 90% confidence
// const z = 1.959963984540 // 95% confidence
const z = 3.090232306168 // 98% confidence
function confidence (s, n) {
if (n === 0) {
return 0
}
const p = s / n
const left = p + 1 / (2 * n) * z * z
const right = z * Math.sqrt(p * (1 - p) / n + z * z / (4 * n * n))
const under = 1 + 1 / n * z * z
return (left - right) / under
}
console.log(confidence(process.argv[2], process.argv[3]))
/*
Need to describe how they'll earn
If we trust upvotes how can we use that to determine the best
*/

56
worker/trust.js
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@ -12,6 +12,8 @@ function trust ({ boss, models }) {
// only explore a path up to this depth from start
const MAX_DEPTH = 6
const MAX_TRUST = 0.9
// https://en.wikipedia.org/wiki/Normal_distribution#Quantile_function
const Z_CONFIDENCE = 2.326347874041 // 98% confidence
function pathsOverlap (arr1 = [], arr2 = []) {
const dp = new Array(arr1.length + 1).fill(0).map(() => new Array(arr2.length + 1).fill(0))
@ -135,6 +137,7 @@ function trustGivenGraph (graph, start) {
}
/*
OLD TRUST GRAPH
graph is returned as json in adjacency list where edges are the trust value 0-.9
graph = {
node1 : [{node : node2, trust: trust12}, {node: node3, trust: trust13}],
@ -142,20 +145,57 @@ function trustGivenGraph (graph, start) {
node3 : [{node : node2, trust: trust32}],
}
*/
// async function getGraph (models) {
// const [{ graph }] = await models.$queryRaw`
// select json_object_agg(id, hops) as graph
// from (
// select id, json_agg(json_build_object('node', oid, 'trust', trust)) as hops
// from (
// select "ItemAct"."userId" as id, "Item"."userId" as oid, least(${MAX_TRUST},
// sum(POWER(.99, EXTRACT(DAY FROM (NOW_UTC() - "ItemAct".created_at))))/21.0) as trust
// from "ItemAct"
// join "Item" on "itemId" = "Item".id and "ItemAct"."userId" <> "Item"."userId"
// where "ItemAct".act = 'VOTE' group by "ItemAct"."userId", "Item"."userId"
// ) a
// group by id
// ) b`
// return graph
// }
// upvote confidence graph
async function getGraph (models) {
const [{ graph }] = await models.$queryRaw`
select json_object_agg(id, hops) as graph
from (
select id, json_agg(json_build_object('node', oid, 'trust', trust)) as hops
from (
select "ItemAct"."userId" as id, "Item"."userId" as oid, least(${MAX_TRUST},
sum(POWER(.99, EXTRACT(DAY FROM (NOW_UTC() - "ItemAct".created_at))))/21.0) as trust
from "ItemAct"
join "Item" on "itemId" = "Item".id and "ItemAct"."userId" <> "Item"."userId"
where "ItemAct".act = 'VOTE' group by "ItemAct"."userId", "Item"."userId"
) a
group by id
) b`
select s.id, s.oid, confidence(s.shared, count(*), ${Z_CONFIDENCE}) as trust
from (
select a."userId" as id, b."userId" as oid, count(*) as shared
from "ItemAct" b
join users bu on bu.id = b."userId"
join "ItemAct" a on b."itemId" = a."itemId"
join users au on au.id = a."userId"
join "Item" on "Item".id = b."itemId"
where b.act = 'VOTE'
and a.act = 'VOTE'
and "Item"."parentId" is null
and "Item"."userId" <> b."userId"
and "Item"."userId" <> a."userId"
and b."userId" <> a."userId"
and "Item".created_at >= au.created_at and "Item".created_at >= bu.created_at
group by b."userId", a."userId") s
join users u on s.id = u.id
join users ou on s.oid = ou.id
join "ItemAct" on "ItemAct"."userId" = s.oid
join "Item" on "Item".id = "ItemAct"."itemId"
where "ItemAct".act = 'VOTE' and "Item"."parentId" is null
and "Item"."userId" <> s.oid and "Item"."userId" <> s.id
and "Item".created_at >= u.created_at and "Item".created_at >= ou.created_at
group by s.id, s.oid, s.shared
) a
group by id
) b`
return graph
}