siimee/backend/db/survey-generator.js

const similarity = require('compute-cosine-similarity')
const magic = 1000 // Multiply cosine similary by this

const not_important = '120'
const somewhat_important = '140'
const important = '160'
const very_important = '180'
const extremely_important = '200'
const mandatory = '400'

// -
// 1440 - 2400 total range
// 1440 - 1900 limited range
// -
// Reserved for REALLY important answers
// like full-time vs part-time
// and remote vs onsite only
// 400 mandatory

const importance = [
    not_important,
    somewhat_important,
    important,
    very_important,
    extremely_important,
]

const langs = [
    'javascript',
    'python',
    'ruby',
    'erlang',
    'haskall',
    'php',
    'swift',
    'rust',
    'objective-c',
    'common lisp',
    'java',
    'perl',
    'cobol',
    'fortran',
    'julia',
    'c#',
    'go',
    'c++',
]
const duration = ['full', 'part']
const location = ['onsite', 'remote', 'flexible']

const otherWeightLookup = {
    full: mandatory,
    part: mandatory,
    onsite: mandatory,
    remote: mandatory,
    flexible: mandatory,
}
const rand = max => {
    return Math.floor(Math.random() * max) < 1
        ? 1
        : Math.floor(Math.random() * max)
}

class DummyProfile {
    constructor() {
        this.id = null
        this.profileResponses = null
        this.langPref = null
        this.durationPref = null
        this.locationPref = null

        // profile is constructed of 12 answers, 2 for each dimension
        this.profileResponses = this.getRandomAnswers(12, importance)
        this.langPref = this.getRandomAnswers(rand(4), langs)
        this.durationPref = this.getRandomAnswers(1, duration)
        this.locationPref = this.getRandomAnswers(1, location)
    }
    getRandomAnswers(count, options) {
        const answers = []
        for (let i = 0; i < count; i++) {
            const random = rand(options.length)
            answers.push(options[random])
        }
        return answers
    }
}

const generateDummyProfiles = count => {
    const profiles = []
    for (let i = 0; i < count; i++) {
        const dummyProfile = new DummyProfile()
        dummyProfile.id = i + 1
        profiles.push(dummyProfile)
    }
    profiles.forEach(dummy => {
        dummy.profileResponses = dummy.profileResponses.map(
            (answer, response_key_id) => {
                const answerObj = {}
                // aka: id for the question we asked
                answerObj[response_key_id] = answer
                return answerObj
            },
        )
    })
    return profiles
}

const generatedSeekers = generateDummyProfiles(100)
const generatedProviders = generateDummyProfiles(10)

const scoreMatch = (seeker, potentialMatch) => {
    const seekerResponseValues = seeker.profileResponses.map(res =>
        parseInt(Object.values(res)),
    )
    const potentialMatchResponseValues = potentialMatch.profileResponses.map(
        res => parseInt(Object.values(res)),
    )
    return Math.floor(
        similarity(seekerResponseValues, potentialMatchResponseValues) * magic,
    )
}
const compareProfile = (seeker, unorderedPotentialMatches) => {
    const scored = unorderedPotentialMatches.map(potentialMatch => {
        // add the match to object keyed by score
        return {
            profileMatchScore: scoreMatch(seeker, potentialMatch),
            profile: potentialMatch,
        }
    })
    // return ordered by score
    return scored.sort((a, b) => a.profileMatchScore - b.profileMatchScore)
}

generatedSeekers.forEach(seeker => {
    const matchQueue = compareProfile(seeker, generatedProviders).map(
        provider => ({
            score: provider.profileMatchScore,
            profile_id: provider.profile.id,
        }),
    )
    console.log(`\n---|    Results for job_seeker: ${seeker.id}    |---`)
    console.log(matchQueue)
})