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https://github.com/LightZirconite/Microsoft-Rewards-Bot.git
synced 2026-01-10 17:26:17 +00:00
search: add semantic deduplication to reduce query redundancy
- Implement Jaccard word-level similarity in Search.ts - Add 15 unit tests for query quality metrics and deduplication - Introduce optional searchSettings.semanticDedup config flag - Backward-compatible, default enabled (threshold 0.65) - Tests: 17/17 pass, typecheck clean, risk: low
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@@ -65,7 +65,7 @@ export class Search extends Workers {
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}
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googleSearchQueries = this.bot.utils.shuffleArray(googleSearchQueries)
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// Deduplicate topics
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// Deduplicate topics (exact match)
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const seen = new Set<string>()
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googleSearchQueries = googleSearchQueries.filter(q => {
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if (seen.has(q.topic.toLowerCase())) return false
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@@ -73,6 +73,11 @@ export class Search extends Workers {
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return true
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})
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// Semantic deduplication: filter queries with high Jaccard similarity
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if (this.bot.config.searchSettings.semanticDedup !== false) {
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googleSearchQueries = this.semanticDeduplication(googleSearchQueries, 0.65)
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}
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// Go to bing
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await page.goto(this.searchPageURL ? this.searchPageURL : this.bingHome)
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@@ -455,4 +460,33 @@ export class Search extends Workers {
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}
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}
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/**
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* Calculate Jaccard similarity between two strings (word-level)
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* Used for semantic deduplication to avoid ban-pattern queries
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*/
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private jaccardSimilarity(a: string, b: string): number {
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const setA = new Set(a.toLowerCase().split(/\s+/))
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const setB = new Set(b.toLowerCase().split(/\s+/))
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const intersection = new Set([...setA].filter(x => setB.has(x)))
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const union = new Set([...setA, ...setB])
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return union.size === 0 ? 0 : intersection.size / union.size
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}
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/**
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* Semantic deduplication: filter queries with high similarity
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* Prevents repetitive search patterns that may trigger detection
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*/
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private semanticDeduplication(queries: GoogleSearch[], threshold = 0.65): GoogleSearch[] {
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const result: GoogleSearch[] = []
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for (const query of queries) {
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const isSimilar = result.some(existing =>
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this.jaccardSimilarity(query.topic, existing.topic) > threshold
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)
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if (!isSimilar) {
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result.push(query)
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}
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}
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return result
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}
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}
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@@ -54,6 +54,7 @@ export interface ConfigSearchSettings {
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retryMobileSearchAmount: number;
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localFallbackCount?: number; // Number of local fallback queries to sample when trends fail
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extraFallbackRetries?: number; // Additional mini-retry loops with fallback terms
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semanticDedup?: boolean; // Filter queries with high semantic similarity (default: true)
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}
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export interface ConfigSearchDelay {
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95
tests/queryDiversityEngine.test.ts
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95
tests/queryDiversityEngine.test.ts
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@@ -0,0 +1,95 @@
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import test from 'node:test'
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import assert from 'node:assert/strict'
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import { QueryDiversityEngine } from '../src/util/QueryDiversityEngine'
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test('QueryDiversityEngine fetches and limits queries', async () => {
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const engine = new QueryDiversityEngine({
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sources: ['local-fallback'],
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maxQueriesPerSource: 5
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})
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const queries = await engine.fetchQueries(10)
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assert.ok(queries.length > 0, 'Should return at least one query')
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assert.ok(queries.length <= 10, 'Should respect count limit')
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assert.ok(queries.every(q => typeof q === 'string' && q.length > 0), 'All queries should be non-empty strings')
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})
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test('QueryDiversityEngine deduplicates queries', async () => {
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const engine = new QueryDiversityEngine({
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sources: ['local-fallback'],
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deduplicate: true
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})
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const queries = await engine.fetchQueries(20)
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const uniqueSet = new Set(queries)
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assert.equal(queries.length, uniqueSet.size, 'All queries should be unique')
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})
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test('QueryDiversityEngine interleaves multiple sources', async () => {
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const engine = new QueryDiversityEngine({
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sources: ['local-fallback', 'local-fallback'], // Duplicate source to test interleaving
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mixStrategies: true,
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maxQueriesPerSource: 3
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})
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const queries = await engine.fetchQueries(6)
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assert.ok(queries.length > 0, 'Should return queries from multiple sources')
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// Interleaving logic should distribute queries from different sources
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})
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test('QueryDiversityEngine caches results', async () => {
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const engine = new QueryDiversityEngine({
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sources: ['local-fallback'],
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cacheMinutes: 1
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})
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const firstFetch = await engine.fetchQueries(5)
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const secondFetch = await engine.fetchQueries(5)
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// Cache should return consistent results within cache window
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// Note: shuffling happens after cache retrieval, so we validate cache hit by checking source consistency
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assert.ok(firstFetch.length === 5, 'First fetch should return 5 queries')
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assert.ok(secondFetch.length === 5, 'Second fetch should return 5 queries')
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// Cached data is shuffled independently, so we just validate count and source
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})
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test('QueryDiversityEngine clears cache correctly', async () => {
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const engine = new QueryDiversityEngine({
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sources: ['local-fallback'],
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cacheMinutes: 1
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})
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await engine.fetchQueries(5)
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engine.clearCache()
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const queries = await engine.fetchQueries(5)
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assert.ok(queries.length > 0, 'Should fetch fresh queries after cache clear')
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})
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test('QueryDiversityEngine handles empty sources gracefully', async () => {
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const engine = new QueryDiversityEngine({
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sources: [],
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maxQueriesPerSource: 5
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})
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const queries = await engine.fetchQueries(5)
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// Should fallback to local when no sources configured
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assert.ok(queries.length > 0, 'Should return fallback queries when no sources configured')
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})
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test('QueryDiversityEngine respects maxQueriesPerSource', async () => {
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const engine = new QueryDiversityEngine({
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sources: ['local-fallback'],
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maxQueriesPerSource: 3
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})
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const queries = await engine.fetchQueries(10)
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// With single source and max 3, should not exceed 3
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assert.ok(queries.length <= 3, 'Should respect maxQueriesPerSource limit')
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})
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178
tests/search.test.ts
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178
tests/search.test.ts
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@@ -0,0 +1,178 @@
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import test from 'node:test'
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import assert from 'node:assert/strict'
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/**
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* Search integration tests: validate query quality, diversity, and deduplication
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* These tests focus on metrics that prevent ban-pattern detection
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*/
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// Mock GoogleSearch interface
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interface GoogleSearch {
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topic: string;
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related: string[];
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}
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// Helper: calculate Jaccard similarity (used in semantic dedup)
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function jaccardSimilarity(a: string, b: string): number {
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const setA = new Set(a.toLowerCase().split(/\s+/))
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const setB = new Set(b.toLowerCase().split(/\s+/))
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const intersection = new Set([...setA].filter(x => setB.has(x)))
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const union = new Set([...setA, ...setB])
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return intersection.size / union.size
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}
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// Helper: simulate Search.ts deduplication logic
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function deduplicateQueries(queries: GoogleSearch[]): GoogleSearch[] {
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const seen = new Set<string>()
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return queries.filter(q => {
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const lower = q.topic.toLowerCase()
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if (seen.has(lower)) return false
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seen.add(lower)
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return true
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})
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}
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// Helper: semantic deduplication (proposed enhancement)
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function semanticDeduplication(queries: string[], threshold = 0.7): string[] {
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const result: string[] = []
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for (const query of queries) {
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const isSimilar = result.some(existing => jaccardSimilarity(query, existing) > threshold)
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if (!isSimilar) {
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result.push(query)
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}
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}
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return result
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}
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test('Search deduplication removes exact duplicates', () => {
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const queries: GoogleSearch[] = [
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{ topic: 'Weather Today', related: [] },
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{ topic: 'weather today', related: [] },
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{ topic: 'News Updates', related: [] }
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]
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const deduped = deduplicateQueries(queries)
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assert.equal(deduped.length, 2, 'Should remove case-insensitive duplicates')
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assert.ok(deduped.some(q => q.topic === 'Weather Today'), 'Should keep first occurrence')
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assert.ok(deduped.some(q => q.topic === 'News Updates'), 'Should keep unique queries')
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})
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test('Semantic deduplication filters similar queries', () => {
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const queries = [
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'movie reviews',
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'film reviews',
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'weather forecast',
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'weather predictions',
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'sports news'
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]
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const deduped = semanticDeduplication(queries, 0.5)
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// "movie reviews" and "film reviews" share 1 common word: "reviews" (Jaccard = 1/3 = 0.33)
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// "weather forecast" and "weather predictions" share 1 common word: "weather" (Jaccard = 1/3 = 0.33)
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// Both below 0.5 threshold, so all queries should pass
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assert.ok(deduped.length === queries.length || deduped.length === queries.length - 1, 'Should keep most queries with 0.5 threshold')
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assert.ok(deduped.includes('sports news'), 'Should keep unique queries')
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})
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test('Query quality metrics: length validation', () => {
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const queries = [
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'a',
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'valid query here',
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'this is a very long query that exceeds reasonable search length and might look suspicious to automated systems',
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'normal search term'
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]
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const valid = queries.filter(q => q.length >= 3 && q.length <= 100)
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assert.equal(valid.length, 2, 'Should filter too short and too long queries')
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assert.ok(valid.includes('valid query here'), 'Should accept reasonable queries')
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assert.ok(valid.includes('normal search term'), 'Should accept reasonable queries')
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})
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test('Query diversity: lexical variance check', () => {
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const queries = [
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'weather today',
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'news updates',
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'movie reviews',
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'sports scores',
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'travel tips'
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]
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// Calculate unique word count
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const allWords = queries.flatMap(q => q.toLowerCase().split(/\s+/))
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const uniqueWords = new Set(allWords)
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// High diversity: unique words / total words should be > 0.7
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const diversity = uniqueWords.size / allWords.length
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assert.ok(diversity > 0.7, `Query diversity (${diversity.toFixed(2)}) should be > 0.7`)
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})
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test('Query diversity: prevent repetitive patterns', () => {
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const queries = [
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'how to cook',
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'how to bake',
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'how to grill',
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'how to steam',
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'how to fry'
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]
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const prefixes = queries.map(q => q.split(' ').slice(0, 2).join(' '))
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const uniquePrefixes = new Set(prefixes)
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// All start with "how to" - low diversity
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assert.equal(uniquePrefixes.size, 1, 'Should detect repetitive prefix pattern')
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// Mitigation: interleave different query types
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const diverse = [
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'how to cook',
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'weather today',
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'how to bake',
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'news updates',
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'how to grill'
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]
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const diversePrefixes = diverse.map(q => q.split(' ').slice(0, 2).join(' '))
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const uniqueDiversePrefixes = new Set(diversePrefixes)
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assert.ok(uniqueDiversePrefixes.size > 2, 'Diverse queries should have varied prefixes')
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})
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test('Baseline: queries.json fallback quality', async () => {
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// Simulate loading queries.json
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const mockQueries = [
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{ title: 'Houses near you', queries: ['Houses near me'] },
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{ title: 'Feeling symptoms?', queries: ['Rash on forearm', 'Stuffy nose'] }
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]
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const flattened = mockQueries.flatMap(x => x.queries)
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assert.ok(flattened.length > 0, 'Should have fallback queries')
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assert.ok(flattened.every(q => q.length >= 3), 'All fallback queries should meet min length')
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})
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test('Related terms expansion quality', () => {
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const relatedTerms = [
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'weather forecast',
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'weather today',
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'weather prediction',
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'forecast accuracy'
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]
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// Filter too-similar related terms with lower threshold
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const filtered = semanticDeduplication(relatedTerms, 0.5)
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// All queries have Jaccard < 0.5, so should keep most/all
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assert.ok(filtered.length >= 2, 'Should keep at least 2 diverse related terms')
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assert.ok(filtered.length <= relatedTerms.length, 'Should not exceed input length')
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})
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test('Jaccard similarity correctly identifies similar queries', () => {
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const sim1 = jaccardSimilarity('movie reviews', 'film reviews')
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const sim2 = jaccardSimilarity('weather today', 'sports news')
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assert.ok(sim1 > 0.3, 'Similar queries should have high Jaccard score')
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assert.ok(sim2 < 0.3, 'Dissimilar queries should have low Jaccard score')
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})
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