trust algo v4
This commit is contained in:
keyan
parent
56dc0568e0
commit
8350b1df3b
167
package-lock.json
generated
167
package-lock.json
generated
@ -35,6 +35,7 @@
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@ -6055,6 +6068,11 @@
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@ -6573,6 +6591,11 @@
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@ -7887,6 +7910,18 @@
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@ -9466,6 +9501,11 @@
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@ -10122,6 +10162,44 @@
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"url": "https://github.com/sponsors/wooorm"
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@ -14319,6 +14397,11 @@
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@ -23432,6 +23543,11 @@
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||||||
|
"fraction.js": {
|
||||||
|
"version": "4.2.0",
|
||||||
|
"resolved": "https://registry.npmjs.org/fraction.js/-/fraction.js-4.2.0.tgz",
|
||||||
|
"integrity": "sha512-MhLuK+2gUcnZe8ZHlaaINnQLl0xRIGRfcGk2yl8xoQAfHrSsL3rYu6FCmBdkdbhc9EPlwyGHewaRsvwRMJtAlA=="
|
||||||
|
},
|
||||||
"fresh": {
|
"fresh": {
|
||||||
"version": "0.5.2",
|
"version": "0.5.2",
|
||||||
"resolved": "https://registry.npmjs.org/fresh/-/fresh-0.5.2.tgz",
|
"resolved": "https://registry.npmjs.org/fresh/-/fresh-0.5.2.tgz",
|
||||||
@ -24583,6 +24699,11 @@
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
|
"javascript-natural-sort": {
|
||||||
|
"version": "0.7.1",
|
||||||
|
"resolved": "https://registry.npmjs.org/javascript-natural-sort/-/javascript-natural-sort-0.7.1.tgz",
|
||||||
|
"integrity": "sha512-nO6jcEfZWQXDhOiBtG2KvKyEptz7RVbpGP4vTD2hLBdmNQSsCiicO2Ioinv6UI4y9ukqnBpy+XZ9H6uLNgJTlw=="
|
||||||
|
},
|
||||||
"jmespath": {
|
"jmespath": {
|
||||||
"version": "0.16.0",
|
"version": "0.16.0",
|
||||||
"resolved": "https://registry.npmjs.org/jmespath/-/jmespath-0.16.0.tgz",
|
"resolved": "https://registry.npmjs.org/jmespath/-/jmespath-0.16.0.tgz",
|
||||||
@ -25116,6 +25237,37 @@
|
|||||||
"resolved": "https://registry.npmjs.org/markdown-table/-/markdown-table-3.0.2.tgz",
|
"resolved": "https://registry.npmjs.org/markdown-table/-/markdown-table-3.0.2.tgz",
|
||||||
"integrity": "sha512-y8j3a5/DkJCmS5x4dMCQL+OR0+2EAq3DOtio1COSHsmW2BGXnNCK3v12hJt1LrUz5iZH5g0LmuYOjDdI+czghA=="
|
"integrity": "sha512-y8j3a5/DkJCmS5x4dMCQL+OR0+2EAq3DOtio1COSHsmW2BGXnNCK3v12hJt1LrUz5iZH5g0LmuYOjDdI+czghA=="
|
||||||
},
|
},
|
||||||
|
"mathjs": {
|
||||||
|
"version": "11.8.2",
|
||||||
|
"resolved": "https://registry.npmjs.org/mathjs/-/mathjs-11.8.2.tgz",
|
||||||
|
"integrity": "sha512-ZePu0oDbM0vuFExikIMY/9syjo/jbgNbX6ti+iMdaALDuxciMCsXIslGDBEn7QCpCWYBiVCYmc0lsmk5bwHBdQ==",
|
||||||
|
"requires": {
|
||||||
|
"@babel/runtime": "^7.22.5",
|
||||||
|
"complex.js": "^2.1.1",
|
||||||
|
"decimal.js": "^10.4.3",
|
||||||
|
"escape-latex": "^1.2.0",
|
||||||
|
"fraction.js": "^4.2.0",
|
||||||
|
"javascript-natural-sort": "^0.7.1",
|
||||||
|
"seedrandom": "^3.0.5",
|
||||||
|
"tiny-emitter": "^2.1.0",
|
||||||
|
"typed-function": "^4.1.0"
|
||||||
|
},
|
||||||
|
"dependencies": {
|
||||||
|
"@babel/runtime": {
|
||||||
|
"version": "7.22.6",
|
||||||
|
"resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.22.6.tgz",
|
||||||
|
"integrity": "sha512-wDb5pWm4WDdF6LFUde3Jl8WzPA+3ZbxYqkC6xAXuD3irdEHN1k0NfTRrJD8ZD378SJ61miMLCqIOXYhd8x+AJQ==",
|
||||||
|
"requires": {
|
||||||
|
"regenerator-runtime": "^0.13.11"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"regenerator-runtime": {
|
||||||
|
"version": "0.13.11",
|
||||||
|
"resolved": "https://registry.npmjs.org/regenerator-runtime/-/regenerator-runtime-0.13.11.tgz",
|
||||||
|
"integrity": "sha512-kY1AZVr2Ra+t+piVaJ4gxaFaReZVH40AKNo7UCX6W+dEwBo/2oZJzqfuN1qLq1oL45o56cPaTXELwrTh8Fpggg=="
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
"md5.js": {
|
"md5.js": {
|
||||||
"version": "1.3.5",
|
"version": "1.3.5",
|
||||||
"resolved": "https://registry.npmjs.org/md5.js/-/md5.js-1.3.5.tgz",
|
"resolved": "https://registry.npmjs.org/md5.js/-/md5.js-1.3.5.tgz",
|
||||||
@ -28138,6 +28290,11 @@
|
|||||||
"resolved": "https://registry.npmjs.org/secure-json-parse/-/secure-json-parse-2.5.0.tgz",
|
"resolved": "https://registry.npmjs.org/secure-json-parse/-/secure-json-parse-2.5.0.tgz",
|
||||||
"integrity": "sha512-ZQruFgZnIWH+WyO9t5rWt4ZEGqCKPwhiw+YbzTwpmT9elgLrLcfuyUiSnwwjUiVy9r4VM3urtbNF1xmEh9IL2w=="
|
"integrity": "sha512-ZQruFgZnIWH+WyO9t5rWt4ZEGqCKPwhiw+YbzTwpmT9elgLrLcfuyUiSnwwjUiVy9r4VM3urtbNF1xmEh9IL2w=="
|
||||||
},
|
},
|
||||||
|
"seedrandom": {
|
||||||
|
"version": "3.0.5",
|
||||||
|
"resolved": "https://registry.npmjs.org/seedrandom/-/seedrandom-3.0.5.tgz",
|
||||||
|
"integrity": "sha512-8OwmbklUNzwezjGInmZ+2clQmExQPvomqjL7LFqOYqtmuxRgQYqOD3mHaU+MvZn5FLUeVxVfQjwLZW/n/JFuqg=="
|
||||||
|
},
|
||||||
"semver": {
|
"semver": {
|
||||||
"version": "6.3.0",
|
"version": "6.3.0",
|
||||||
"resolved": "https://registry.npmjs.org/semver/-/semver-6.3.0.tgz",
|
"resolved": "https://registry.npmjs.org/semver/-/semver-6.3.0.tgz",
|
||||||
@ -29186,6 +29343,11 @@
|
|||||||
"resolved": "https://registry.npmjs.org/timeout-refresh/-/timeout-refresh-2.0.1.tgz",
|
"resolved": "https://registry.npmjs.org/timeout-refresh/-/timeout-refresh-2.0.1.tgz",
|
||||||
"integrity": "sha512-SVqEcMZBsZF9mA78rjzCrYrUs37LMJk3ShZ851ygZYW1cMeIjs9mL57KO6Iv5mmjSQnOe/29/VAfGXo+oRCiVw=="
|
"integrity": "sha512-SVqEcMZBsZF9mA78rjzCrYrUs37LMJk3ShZ851ygZYW1cMeIjs9mL57KO6Iv5mmjSQnOe/29/VAfGXo+oRCiVw=="
|
||||||
},
|
},
|
||||||
|
"tiny-emitter": {
|
||||||
|
"version": "2.1.0",
|
||||||
|
"resolved": "https://registry.npmjs.org/tiny-emitter/-/tiny-emitter-2.1.0.tgz",
|
||||||
|
"integrity": "sha512-NB6Dk1A9xgQPMoGqC5CVXn123gWyte215ONT5Pp5a0yt4nlEoO1ZWeCwpncaekPHXO60i47ihFnZPiRPjRMq4Q=="
|
||||||
|
},
|
||||||
"tiny-secp256k1": {
|
"tiny-secp256k1": {
|
||||||
"version": "2.2.1",
|
"version": "2.2.1",
|
||||||
"resolved": "https://registry.npmjs.org/tiny-secp256k1/-/tiny-secp256k1-2.2.1.tgz",
|
"resolved": "https://registry.npmjs.org/tiny-secp256k1/-/tiny-secp256k1-2.2.1.tgz",
|
||||||
@ -29378,6 +29540,11 @@
|
|||||||
"mime-types": "~2.1.24"
|
"mime-types": "~2.1.24"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
|
"typed-function": {
|
||||||
|
"version": "4.1.0",
|
||||||
|
"resolved": "https://registry.npmjs.org/typed-function/-/typed-function-4.1.0.tgz",
|
||||||
|
"integrity": "sha512-DGwUl6cioBW5gw2L+6SMupGwH/kZOqivy17E4nsh1JI9fKF87orMmlQx3KISQPmg3sfnOUGlwVkroosvgddrlg=="
|
||||||
|
},
|
||||||
"typeforce": {
|
"typeforce": {
|
||||||
"version": "1.18.0",
|
"version": "1.18.0",
|
||||||
"resolved": "https://registry.npmjs.org/typeforce/-/typeforce-1.18.0.tgz",
|
"resolved": "https://registry.npmjs.org/typeforce/-/typeforce-1.18.0.tgz",
|
||||||
|
|||||||
@ -36,6 +36,7 @@
|
|||||||
"jquery": "^3.6.1",
|
"jquery": "^3.6.1",
|
||||||
"lexical": "^0.7.5",
|
"lexical": "^0.7.5",
|
||||||
"ln-service": "^54.2.6",
|
"ln-service": "^54.2.6",
|
||||||
|
"mathjs": "^11.8.2",
|
||||||
"mdast-util-find-and-replace": "^1.1.1",
|
"mdast-util-find-and-replace": "^1.1.1",
|
||||||
"mdast-util-from-markdown": "^1.2.0",
|
"mdast-util-from-markdown": "^1.2.0",
|
||||||
"mdast-util-to-string": "^3.1.0",
|
"mdast-util-to-string": "^3.1.0",
|
||||||
|
|||||||
304
worker/trust.js
304
worker/trust.js
@ -1,239 +1,157 @@
|
|||||||
|
const math = require('mathjs')
|
||||||
|
|
||||||
function trust ({ boss, models }) {
|
function trust ({ boss, models }) {
|
||||||
return async function () {
|
return async function () {
|
||||||
console.log('doing trust')
|
try {
|
||||||
|
console.time('trust')
|
||||||
|
console.timeLog('trust', 'getting graph')
|
||||||
const graph = await getGraph(models)
|
const graph = await getGraph(models)
|
||||||
const user = await models.user.findUnique({ where: { name: process.env.WOT_SOURCE || 'k00b' } })
|
console.timeLog('trust', 'computing trust')
|
||||||
const trust = await trustGivenGraph(graph, user.id)
|
const trust = await trustGivenGraph(graph)
|
||||||
|
console.timeLog('trust', 'storing trust')
|
||||||
await storeTrust(models, trust)
|
await storeTrust(models, trust)
|
||||||
console.log('done doing trust')
|
console.timeEnd('trust')
|
||||||
|
} catch (e) {
|
||||||
|
console.error(e)
|
||||||
|
throw e
|
||||||
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// only explore a path up to this depth from start
|
const MAX_DEPTH = 10
|
||||||
const MAX_DEPTH = 6
|
const MAX_TRUST = 1
|
||||||
const MAX_TRUST = 0.9
|
const MIN_SUCCESS = 1
|
||||||
const MIN_SUCCESS = 5
|
// increasing disgree_mult increases distrust when there's disagreement
|
||||||
// increasing disgree_mult increases distrust when there's disagreement, at 1x we double count disagreement,
|
// ... this cancels DISAGREE_MULT number of "successes" for every disagreement
|
||||||
// at 2x we triple count, etc ... this count is reflected/added in the number of total "trials" between users
|
const DISAGREE_MULT = 10
|
||||||
const DISAGREE_MULT = 1
|
|
||||||
// https://en.wikipedia.org/wiki/Normal_distribution#Quantile_function
|
// https://en.wikipedia.org/wiki/Normal_distribution#Quantile_function
|
||||||
const Z_CONFIDENCE = 2.326347874041 // 98% confidence
|
const Z_CONFIDENCE = 6.109410204869 // 99.9999999% confidence
|
||||||
|
const SEEDS = [616, 6030, 946, 4502]
|
||||||
function pathsOverlap (arr1 = [], arr2 = []) {
|
const SEED_WEIGHT = 0.25
|
||||||
const dp = new Array(arr1.length + 1).fill(0).map(() => new Array(arr2.length + 1).fill(0))
|
const AGAINST_MSAT_MIN = 1000
|
||||||
for (let i = arr1.length - 1; i >= 0; i--) {
|
const MSAT_MIN = 1000
|
||||||
for (let j = arr2.length - 1; j >= 0; j--) {
|
|
||||||
if (arr1[i] === arr2[j]) {
|
|
||||||
dp[i][j] = dp[i + 1][j + 1] + 1
|
|
||||||
if (dp[i][j] > 1) {
|
|
||||||
return true
|
|
||||||
}
|
|
||||||
} else {
|
|
||||||
dp[i][j] = 0
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
return false
|
|
||||||
}
|
|
||||||
|
|
||||||
/*
|
|
||||||
This approximates an upper bound of trust given a list of indepent trust
|
|
||||||
values ... we basically are compressing a trust vector into a single value
|
|
||||||
without having to compute the trust using the inclusion-exclusion principle
|
|
||||||
*/
|
|
||||||
function boundedTrust (probs) {
|
|
||||||
const max = Math.max(...probs)
|
|
||||||
const sum = probs.reduce((a, c) => a + c)
|
|
||||||
const trust = sum - max * (sum - max)
|
|
||||||
return Math.min(trust, MAX_TRUST)
|
|
||||||
}
|
|
||||||
|
|
||||||
/*
|
|
||||||
Given the paths to each node and the accumulated trust along that path
|
|
||||||
this function returns an object where the keys are the node ids and
|
|
||||||
their value is the trust of that node
|
|
||||||
*/
|
|
||||||
function trustGivenPaths (paths) {
|
|
||||||
const trust = {}
|
|
||||||
for (const [node, npaths] of Object.entries(paths)) {
|
|
||||||
trust[node] = boundedTrust(Object.values(npaths))
|
|
||||||
}
|
|
||||||
return trust
|
|
||||||
}
|
|
||||||
|
|
||||||
/*
|
/*
|
||||||
Given a graph and start this function returns an object where
|
Given a graph and start this function returns an object where
|
||||||
the keys are the node id and their value is the trust of that node
|
the keys are the node id and their value is the trust of that node
|
||||||
*/
|
*/
|
||||||
function trustGivenGraph (graph, start) {
|
function trustGivenGraph (graph) {
|
||||||
const queue = [] // queue of to be visited nodes
|
// empty matrix of proper size nstackers x nstackers
|
||||||
queue.push(start) // visit start first
|
const mat = math.zeros(graph.length, graph.length, 'sparse')
|
||||||
|
|
||||||
const depth = {} // store the node depth ... XXX space inefficient
|
// create a map of user id to position in matrix
|
||||||
depth[start] = 0 // start node is depth 0
|
const posByUserId = {}
|
||||||
|
for (const [idx, val] of graph.entries()) {
|
||||||
const paths = {} // { node : { path to node as stringified json array : trust } }
|
posByUserId[val.id] = idx
|
||||||
paths[start] = { '[]': 1 } // the paths to start is an empty path with trust of 1
|
|
||||||
|
|
||||||
// while we have nodes to visit
|
|
||||||
while (queue.length > 0) {
|
|
||||||
const node = queue.shift()
|
|
||||||
if (depth[node] === MAX_DEPTH) break
|
|
||||||
|
|
||||||
if (!graph[node]) {
|
|
||||||
// node doesn't have outbound edges
|
|
||||||
continue
|
|
||||||
}
|
}
|
||||||
|
|
||||||
// for all of this nodes outbound edges
|
// iterate over graph, inserting edges into matrix
|
||||||
for (let i = 0; i < graph[node].length; i++) {
|
for (const [idx, val] of graph.entries()) {
|
||||||
const { node: sibling, trust } = graph[node][i]
|
for (const { node, trust } of val.hops) {
|
||||||
let explore = false
|
try {
|
||||||
|
mat.set([idx, posByUserId[node]], Number(trust))
|
||||||
// for all existing paths to this node
|
} catch (e) {
|
||||||
for (const [key, value] of Object.entries(paths[node])) {
|
console.log('error:', idx, node, posByUserId[node], trust)
|
||||||
const parentPath = JSON.parse(key)
|
throw e
|
||||||
if (parentPath.includes(sibling)) {
|
|
||||||
// sibling already exists on a path to us, ie this would be a cycle
|
|
||||||
continue
|
|
||||||
}
|
|
||||||
|
|
||||||
// add this path to sibling
|
|
||||||
const path = JSON.stringify([...parentPath, node])
|
|
||||||
paths[sibling] = paths[sibling] || {}
|
|
||||||
|
|
||||||
// if this sibling has not been visited along this path
|
|
||||||
if (!paths[sibling][path]) {
|
|
||||||
// here we exclude paths that aren't disjoint - they mininally contribute
|
|
||||||
// to trust so we just exclude them, yielding a very small underestimation
|
|
||||||
// of trust while reducing the number of paths we have to explore
|
|
||||||
let disjoint = true
|
|
||||||
// for all the paths to sibling
|
|
||||||
for (const [key2] of Object.entries(paths[sibling])) {
|
|
||||||
// if this existing path to sibling contains overlap with the
|
|
||||||
// path we're exploring, ignore it
|
|
||||||
const otherPath = JSON.parse(key2)
|
|
||||||
const parsedPath = JSON.parse(path)
|
|
||||||
if (pathsOverlap(otherPath, parsedPath)) {
|
|
||||||
disjoint = false
|
|
||||||
break
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
// if this path is disjoint with all existing paths to sibling
|
|
||||||
if (disjoint) {
|
|
||||||
// accumulate the trust along the path and store it
|
|
||||||
paths[sibling][path] = value * trust
|
|
||||||
explore = true
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// if we shouldn't explore this sibling, don't queue it
|
// perform random walk over trust matrix
|
||||||
if (!explore) continue
|
// the resulting matrix columns represent the trust a user (col) has for each other user (rows)
|
||||||
depth[sibling] = depth[node] + 1
|
// XXX this scales N^3 and mathjs is slow
|
||||||
queue.push(sibling)
|
let matT = math.transpose(mat)
|
||||||
}
|
const original = matT.clone()
|
||||||
|
for (let i = 0; i < MAX_DEPTH; i++) {
|
||||||
|
console.timeLog('trust', `matrix multiply ${i}`)
|
||||||
|
matT = math.multiply(original, matT)
|
||||||
|
matT = math.add(math.multiply(1 - SEED_WEIGHT, matT), math.multiply(SEED_WEIGHT, original))
|
||||||
}
|
}
|
||||||
|
|
||||||
return trustGivenPaths(paths)
|
console.timeLog('trust', 'normalizing result')
|
||||||
|
// we normalize the result taking the z-score, then min-max to [0,1]
|
||||||
|
// we remove seeds and 0 trust people from the result because they are known outliers
|
||||||
|
// but we need to keep them in the result to keep positions correct
|
||||||
|
function resultForId (id) {
|
||||||
|
let result = math.squeeze(math.subset(math.transpose(matT), math.index(posByUserId[id], math.range(0, graph.length))))
|
||||||
|
const outliers = SEEDS.concat([id])
|
||||||
|
outliers.forEach(id => result.set([posByUserId[id]], 0))
|
||||||
|
const withoutZero = math.filter(result, val => val > 0)
|
||||||
|
// NOTE: this might be improved by using median and mad (modified z score)
|
||||||
|
// given the distribution is skewed
|
||||||
|
const mean = math.mean(withoutZero)
|
||||||
|
const std = math.std(withoutZero)
|
||||||
|
result = result.map(val => val >= 0 ? (val - mean) / std : 0)
|
||||||
|
const min = math.min(result)
|
||||||
|
const max = math.max(result)
|
||||||
|
result = math.map(result, val => (val - min) / (max - min))
|
||||||
|
outliers.forEach(id => result.set([posByUserId[id]], MAX_TRUST))
|
||||||
|
return result
|
||||||
|
}
|
||||||
|
|
||||||
|
// turn the result vector into an object
|
||||||
|
const result = {}
|
||||||
|
resultForId(616).forEach((val, idx) => {
|
||||||
|
result[graph[idx].id] = val
|
||||||
|
})
|
||||||
|
|
||||||
|
return result
|
||||||
}
|
}
|
||||||
|
|
||||||
/*
|
/*
|
||||||
OLD TRUST GRAPH
|
graph is returned as json in adjacency list where edges are the trust value 0-1
|
||||||
graph is returned as json in adjacency list where edges are the trust value 0-.9
|
graph = [
|
||||||
graph = {
|
{ id: node1, hops: [{node : node2, trust: trust12}, {node: node3, trust: trust13}] },
|
||||||
node1 : [{node : node2, trust: trust12}, {node: node3, trust: trust13}],
|
...
|
||||||
node2 : [{node : node1, trust: trust21}],
|
]
|
||||||
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(${MAX_TRUST},
|
|
||||||
// sum(POWER(.99, EXTRACT(DAY FROM (NOW_UTC() - "ItemAct".created_at))))/21.0) as trust
|
|
||||||
// from "ItemAct"
|
|
||||||
// join "Item" on "itemId" = "Item".id and "ItemAct"."userId" <> "Item"."userId"
|
|
||||||
// where "ItemAct".act = 'VOTE' group by "ItemAct"."userId", "Item"."userId"
|
|
||||||
// ) a
|
|
||||||
// group by id
|
|
||||||
// ) b`
|
|
||||||
// return graph
|
|
||||||
// }
|
|
||||||
|
|
||||||
// old upvote confidence graph
|
|
||||||
// async function getGraph (models) {
|
|
||||||
// const [{ graph }] = await models.$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 s.id, s.oid, confidence(s.shared, count(*), ${Z_CONFIDENCE}) as trust
|
|
||||||
// from (
|
|
||||||
// select a."userId" as id, b."userId" as oid, count(*) as shared
|
|
||||||
// from "ItemAct" b
|
|
||||||
// join users bu on bu.id = b."userId"
|
|
||||||
// join "ItemAct" a on b."itemId" = a."itemId"
|
|
||||||
// join users au on au.id = a."userId"
|
|
||||||
// join "Item" on "Item".id = b."itemId"
|
|
||||||
// where b.act = 'VOTE'
|
|
||||||
// and a.act = 'VOTE'
|
|
||||||
// and "Item"."parentId" is null
|
|
||||||
// and "Item"."userId" <> b."userId"
|
|
||||||
// and "Item"."userId" <> a."userId"
|
|
||||||
// and b."userId" <> a."userId"
|
|
||||||
// and "Item".created_at >= au.created_at and "Item".created_at >= bu.created_at
|
|
||||||
// group by b."userId", a."userId") s
|
|
||||||
// join users u on s.id = u.id
|
|
||||||
// join users ou on s.oid = ou.id
|
|
||||||
// join "ItemAct" on "ItemAct"."userId" = s.oid
|
|
||||||
// join "Item" on "Item".id = "ItemAct"."itemId"
|
|
||||||
// where "ItemAct".act = 'VOTE' and "Item"."parentId" is null
|
|
||||||
// and "Item"."userId" <> s.oid and "Item"."userId" <> s.id
|
|
||||||
// and "Item".created_at >= u.created_at and "Item".created_at >= ou.created_at
|
|
||||||
// group by s.id, s.oid, s.shared
|
|
||||||
// ) a
|
|
||||||
// group by id
|
|
||||||
// ) b`
|
|
||||||
// return graph
|
|
||||||
// }
|
|
||||||
|
|
||||||
async function getGraph (models) {
|
async function getGraph (models) {
|
||||||
const [{ graph }] = await models.$queryRaw`
|
return await models.$queryRaw`
|
||||||
SELECT json_object_agg(id, hops) AS graph
|
SELECT id, array_agg(json_build_object(
|
||||||
FROM (
|
'node', oid,
|
||||||
SELECT id, json_agg(json_build_object('node', oid, 'trust', trust)) AS hops
|
'trust', CASE WHEN total_trust > 0 THEN trust / total_trust::float ELSE 0 END)) AS hops
|
||||||
FROM (
|
FROM (
|
||||||
WITH user_votes AS (
|
WITH user_votes AS (
|
||||||
SELECT "ItemAct"."userId" AS user_id, users.name AS name, "ItemAct"."itemId" AS item_id, min("ItemAct".created_at) AS act_at,
|
SELECT "ItemAct"."userId" AS user_id, users.name AS name, "ItemAct"."itemId" AS item_id, min("ItemAct".created_at) AS act_at,
|
||||||
users.created_at AS user_at, "ItemAct".act = 'DONT_LIKE_THIS' AS against, count(*) OVER (partition by "ItemAct"."userId") AS user_vote_count
|
users.created_at AS user_at, "ItemAct".act = 'DONT_LIKE_THIS' AS against,
|
||||||
|
count(*) OVER (partition by "ItemAct"."userId") AS user_vote_count
|
||||||
FROM "ItemAct"
|
FROM "ItemAct"
|
||||||
JOIN "Item" ON "Item".id = "ItemAct"."itemId" AND "ItemAct".act IN ('FEE', 'TIP', 'DONT_LIKE_THIS') AND "Item"."parentId" IS NULL
|
JOIN "Item" ON "Item".id = "ItemAct"."itemId" AND "ItemAct".act IN ('FEE', 'TIP', 'DONT_LIKE_THIS')
|
||||||
|
AND "Item"."parentId" IS NULL AND NOT "Item".bio AND "Item"."userId" <> "ItemAct"."userId"
|
||||||
JOIN users ON "ItemAct"."userId" = users.id
|
JOIN users ON "ItemAct"."userId" = users.id
|
||||||
GROUP BY user_id, name, item_id, user_at, against
|
GROUP BY user_id, name, item_id, user_at, against
|
||||||
|
HAVING CASE WHEN
|
||||||
|
"ItemAct".act = 'DONT_LIKE_THIS' THEN sum("ItemAct".msats) > ${AGAINST_MSAT_MIN}
|
||||||
|
ELSE sum("ItemAct".msats) > ${MSAT_MIN} END
|
||||||
),
|
),
|
||||||
user_pair AS (
|
user_pair AS (
|
||||||
SELECT a.user_id AS a_id, a.name AS a_name, b.user_id AS b_id, b.name AS b_name,
|
SELECT a.user_id AS a_id, b.user_id AS b_id,
|
||||||
count(*) FILTER(WHERE a.act_at > b.act_at AND a.against = b.against) AS before,
|
count(*) FILTER(WHERE a.act_at > b.act_at AND a.against = b.against) AS before,
|
||||||
count(*) FILTER(WHERE b.act_at > a.act_at AND a.against = b.against) AS after,
|
count(*) FILTER(WHERE b.act_at > a.act_at AND a.against = b.against) AS after,
|
||||||
count(*) FILTER(WHERE a.against <> b.against) * ${DISAGREE_MULT} AS disagree,
|
count(*) FILTER(WHERE a.against <> b.against) * ${DISAGREE_MULT} AS disagree,
|
||||||
CASE WHEN b.user_at > a.user_at THEN b.user_vote_count ELSE a.user_vote_count END AS total
|
b.user_vote_count AS b_total, a.user_vote_count AS a_total
|
||||||
FROM user_votes a
|
FROM user_votes a
|
||||||
JOIN user_votes b ON a.item_id = b.item_id
|
JOIN user_votes b ON a.item_id = b.item_id
|
||||||
GROUP BY a.user_id, a.name, a.user_at, a.user_vote_count, b.user_id, b.name, b.user_at, b.user_vote_count
|
WHERE a.user_id <> b.user_id
|
||||||
)
|
GROUP BY a.user_id, a.user_vote_count, b.user_id, b.user_vote_count
|
||||||
SELECT a_id AS id, a_name, b_id AS oid, b_name, confidence(before, total + disagree - after, ${Z_CONFIDENCE}) AS trust, before, after, disagree, total
|
),
|
||||||
|
trust_pairs AS (
|
||||||
|
SELECT a_id AS id, b_id AS oid,
|
||||||
|
CASE WHEN before - disagree >= ${MIN_SUCCESS} AND b_total - after > 0 THEN
|
||||||
|
confidence(before - disagree, b_total - after, ${Z_CONFIDENCE})
|
||||||
|
ELSE 0 END AS trust
|
||||||
FROM user_pair
|
FROM user_pair
|
||||||
WHERE before >= ${MIN_SUCCESS}
|
WHERE b_id <> ANY (${SEEDS})
|
||||||
|
UNION ALL
|
||||||
|
SELECT a_id AS id, seed_id AS oid, ${MAX_TRUST}::float/ARRAY_LENGTH(${SEEDS}::int[], 1) as trust
|
||||||
|
FROM user_pair, unnest(${SEEDS}::int[]) seed_id
|
||||||
|
GROUP BY a_id, a_total, seed_id
|
||||||
|
)
|
||||||
|
SELECT id, oid, trust, sum(trust) OVER (PARTITION BY id) AS total_trust
|
||||||
|
FROM trust_pairs
|
||||||
) a
|
) a
|
||||||
GROUP BY a.id
|
GROUP BY a.id
|
||||||
) b`
|
ORDER BY id ASC`
|
||||||
return graph
|
|
||||||
}
|
}
|
||||||
|
|
||||||
async function storeTrust (models, nodeTrust) {
|
async function storeTrust (models, nodeTrust) {
|
||||||
|
|||||||
Loading…
x
Reference in New Issue
Block a user