Harden Wordstat source group filtering
This commit is contained in:
DCCONSTRUCTIONS
parent
cebc0d9b7d
commit
50619193f0
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@ -84,6 +84,17 @@ export type KeywordCleaningModelTaskContract = {
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sourceClusterId: string | null;
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sourceClusterTitle: string | null;
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}>;
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sourceGroupCritics: Array<{
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sourcePhrase: string;
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verdict: "clean" | "mixed" | "source_drift";
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reason: string;
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resultCount: number;
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exactCount: number;
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driftSignalCount: number;
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strictFitSignalCount: number;
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driftExamples: string[];
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strictFitExamples: string[];
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}>;
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};
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outputSchema: {
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schemaVersion: "keyword-cleaning.v1";
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@ -95,6 +106,8 @@ export type KeywordCleaningModelTaskContract = {
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broadFrequencyDoesNotOverrideSemanticFit: boolean;
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demoteRelatedWhenDominantFacetMissing: boolean;
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preserveApprovedAnchorFacets: boolean;
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quarantineNoisyRelatedGroups: boolean;
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sourceGroupDriftDoesNotEnterKeywordMap: boolean;
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useRequiresExactEvidence: boolean;
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riskyWhenNoPageBinding: boolean;
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trashWhenOffContext: boolean;
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@ -205,6 +218,22 @@ type RelatedSourceSeed = Pick<
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SeedQueueItem,
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"clusterId" | "clusterTitle" | "normalization" | "phrase" | "priority" | "projectOntologyVersionId" | "source"
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>;
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type WordstatSourceGroupCriticVerdict = "clean" | "mixed" | "source_drift";
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type WordstatSourceGroupCritic = {
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sourcePhrase: string;
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normalizedSourcePhrase: string;
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verdict: WordstatSourceGroupCriticVerdict;
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reason: string;
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resultCount: number;
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exactCount: number;
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signalCount: number;
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driftSignalCount: number;
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strictFitSignalCount: number;
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sourceHasStrictFit: boolean;
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sourceLooksWeak: boolean;
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driftExamples: string[];
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strictFitExamples: string[];
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};
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const HARD_TRASH_PATTERNS = [
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/(^|\s)(ваканси[ия]|работа|зарплата|резюме)(\s|$)/i,
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@ -249,6 +278,26 @@ const PRODUCT_TARIFF_QUALIFIER_PATTERN =
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const AI_KEYWORD_PATTERN = /(^|\s)(ai|ии)(\s|$)|искусственн[а-яёa-z0-9-]*\s+интеллект|нейросет/i;
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const B2B_KEYWORD_FACET_PATTERN =
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/бизнес|процесс|разработ|приложен|агент|ассистент|интеграц|решен|платформ|стоимост|внедрен|купить|заказать|тариф|1с|crm|erp|bpm|workflow|digital|twin|цифров|двойн|bim|бим|инженер|данн|тендер|закуп|юрид|договор|беспилот|iot|телеметр|строител|эксплуатац|проект|офис|облак|оркестр|инфраструктур|безопасн|предприят|корпоратив/i;
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const SOURCE_GROUP_CRITIC_MIN_RESULTS = 4;
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const SOURCE_GROUP_CRITIC_MODEL_LIMIT = 24;
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const SOURCE_GROUP_CRITIC_DRIFT_PATTERNS = [
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/(^|\s)(звук[а-яёa-z0-9-]*|слог[а-яёa-z0-9-]*|букв[а-яёa-z0-9-]*|реч[а-яёa-z0-9-]*|логопед[а-яёa-z0-9-]*|артикуляц[а-яёa-z0-9-]*|дошкольн[а-яёa-z0-9-]*|произношен[а-яёa-z0-9-]*)(\s|$)/i,
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/(^|\s)(основн[а-яёa-z0-9-]*|базов[а-яёa-z0-9-]*)\s+(поняти[а-яёa-z0-9-]*|цель|цели|задач[а-яёa-z0-9-]*|принцип[а-яёa-z0-9-]*|вид[а-яёa-z0-9-]*|тип[а-яёa-z0-9-]*|функци[а-яёa-z0-9-]*|этап[а-яёa-z0-9-]*|направлен[а-яёa-z0-9-]*|уровн[а-яёa-z0-9-]*|средств[а-яёa-z0-9-]*)/i,
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/(^|\s)(поняти[ея]|определен[а-яёa-z0-9-]*|цель|цели|задач[аи]?|принцип[а-яёa-z0-9-]*|виды|типы|функци[а-яёa-z0-9-]*|этапы|направлен[а-яёa-z0-9-]*|уровни|схем[а-яёa-z0-9-]*|структур[а-яёa-z0-9-]*|классификац[а-яёa-z0-9-]*|реферат|конспект|презентац[а-яёa-z0-9-]*)(\s|$)/i,
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/(^|\s)(упражнен[а-яёa-z0-9-]*|задани[а-яёa-z0-9-]*|игр[а-яёa-z0-9-]*|картинк[а-яёa-z0-9-]*|стих[а-яёa-z0-9-]*)(\s|$)/i
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];
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const SOURCE_GROUP_CRITIC_WEAK_SOURCE_PATTERNS = [
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/(^|\s)(предложени[еяюях]*|основн[а-яёa-z0-9-]*|поняти[а-яёa-z0-9-]*|цель|цели|задач[а-яёa-z0-9-]*|принцип[а-яёa-z0-9-]*|вид[а-яёa-z0-9-]*|тип[а-яёa-z0-9-]*|функци[а-яёa-z0-9-]*|этап[а-яёa-z0-9-]*|направлен[а-яёa-z0-9-]*)(\s|$)/i
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];
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const SOURCE_GROUP_STRICT_PRODUCT_FIT_PATTERNS = [
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/(^|\s)(агент[а-яёa-z0-9-]*|ассистент[а-яёa-z0-9-]*)(\s|$)/i,
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/(^|\s)(ai|ии|llm|ml|нейросет[а-яёa-z0-9-]*|искусственн[а-яёa-z0-9-]*\s+интеллект)\s+(агент[а-яёa-z0-9-]*|ассистент[а-яёa-z0-9-]*|платформ[а-яёa-z0-9-]*|решен[а-яёa-z0-9-]*|сервис[а-яёa-z0-9-]*|для\s+(бизнес[а-яёa-z0-9-]*|компан[а-яёa-z0-9-]*|предприят[а-яёa-z0-9-]*|корпоративн[а-яёa-z0-9-]*))/i,
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/(^|\s)(платформ[а-яёa-z0-9-]*|решен[а-яёa-z0-9-]*|сервис[а-яёa-z0-9-]*)\s+(ai|ии|llm|ml|нейросет[а-яёa-z0-9-]*|искусственн[а-яёa-z0-9-]*\s+интеллект)(\s|$)/i,
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/(^|\s)(b2b|enterprise|корпоративн[а-яёa-z0-9-]*|предприят[а-яёa-z0-9-]*|компан[а-яёa-z0-9-]*|бизнес[а-яёa-z0-9-]*)(\s|$)/i,
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/(^|\s)(crm|erp|bpm|workflow|api|1с|1c|эдо|документооборот|закуп[а-яёa-z0-9-]*|тендер[а-яёa-z0-9-]*|договор[а-яёa-z0-9-]*|юридическ[а-яёa-z0-9-]*|финанс[а-яёa-z0-9-]*|поручен[а-яёa-z0-9-]*|согласован[а-яёa-z0-9-]*|база\s+знан[а-яёa-z0-9-]*)(\s|$)/i,
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/(^|\s)(интеграц[а-яёa-z0-9-]*|внедрен[а-яёa-z0-9-]*|разработк[а-яёa-z0-9-]*|под\s+ключ|заказать|купить|стоимост[а-яёa-z0-9-]*|цен[а-яёa-z0-9-]*|платформ[а-яёa-z0-9-]*|решен[а-яёa-z0-9-]*)(\s|$)/i,
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/(^|\s)(строител[а-яёa-z0-9-]*|производств[а-яёa-z0-9-]*|промышленн[а-яёa-z0-9-]*|беспилот[а-яёa-z0-9-]*|iot|телеметр[а-яёa-z0-9-]*|digital\s+twin|цифров[а-яёa-z0-9-]*\s+двойн[а-яёa-z0-9-]*|bim|бим)(\s|$)/i
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];
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const KEYWORD_CLEANING_MODEL_APPROVED_ANCHOR_LIMIT = 60;
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const KEYWORD_CLEANING_MODEL_LANDING_BRIEF_LIMIT = 18;
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const KEYWORD_CLEANING_MODEL_NORMALIZATION_GROUP_LIMIT = 24;
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@ -712,6 +761,233 @@ function promoteExactDemandItems(market: MarketEnrichmentContract, items: Keywor
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});
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}
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function hasProtectedProjectFacet(value: string, guard: KeywordCleaningFacetGuard) {
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const phraseStems = getKeywordCleaningFacetStems(value);
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return guard.dominantProtectedStems.some((facet) => phraseStems.has(facet.stem));
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}
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function hasStrictRelatedProductFit(market: MarketEnrichmentContract, value: string, guard: KeywordCleaningFacetGuard) {
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const normalizedValue = normalizePhrase(value);
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if (hasProtectedProjectFacet(normalizedValue, guard)) {
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return true;
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}
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if (hasPattern(normalizedValue, SOURCE_GROUP_STRICT_PRODUCT_FIT_PATTERNS)) {
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return true;
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}
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return (
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AI_KEYWORD_PATTERN.test(normalizedValue) &&
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hasB2BKeywordFacet(normalizedValue) &&
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!isConsumerAiNoisePhrase(normalizedValue) &&
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!hasEducationIntentMismatch(market, normalizedValue)
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);
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}
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function hasSourceGroupRelatedDriftSignal(market: MarketEnrichmentContract, phrase: string) {
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const normalizedPhrase = normalizePhrase(phrase);
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return (
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hasPattern(normalizedPhrase, SOURCE_GROUP_CRITIC_DRIFT_PATTERNS) ||
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isConsumerAiNoisePhrase(normalizedPhrase) ||
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isOffContextRelatedNoisePhrase(normalizedPhrase) ||
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hasThirdPartyBrandDemandMismatch(normalizedPhrase) ||
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hasNonProductMarketIntentMismatch(normalizedPhrase) ||
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hasEducationIntentMismatch(market, normalizedPhrase)
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);
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}
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function sourceGroupLooksWeak(sourcePhrase: string, guard: KeywordCleaningFacetGuard) {
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const normalizedSourcePhrase = normalizePhrase(sourcePhrase);
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return hasPattern(normalizedSourcePhrase, SOURCE_GROUP_CRITIC_WEAK_SOURCE_PATTERNS) && !hasProtectedProjectFacet(normalizedSourcePhrase, guard);
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}
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function getSourceGroupCriticVerdict(input: {
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driftShare: number;
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driftSignalCount: number;
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signalCount: number;
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sourceHasStrictFit: boolean;
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sourceLooksWeak: boolean;
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strictFitShare: number;
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strictFitSignalCount: number;
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}): WordstatSourceGroupCriticVerdict {
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if (input.signalCount < SOURCE_GROUP_CRITIC_MIN_RESULTS) {
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return "clean";
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}
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if (
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input.sourceLooksWeak &&
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input.driftSignalCount >= 2 &&
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input.strictFitSignalCount <= 1 &&
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input.strictFitShare < 0.5
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) {
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return "source_drift";
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}
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if (!input.sourceHasStrictFit && input.driftShare >= 0.45 && input.strictFitShare < 0.45 && input.signalCount >= 6) {
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return "source_drift";
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}
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if (input.driftShare >= 0.7 && input.strictFitShare < 0.35 && input.signalCount >= 6) {
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return "source_drift";
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}
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if (input.driftShare >= 0.3 && input.strictFitShare < 0.6) {
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return "mixed";
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}
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return "clean";
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}
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function buildWordstatSourceGroupCriticReason(critic: Omit<WordstatSourceGroupCritic, "reason">) {
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if (critic.verdict === "source_drift") {
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return `Source-group critic пометил Wordstat related-группу "${critic.sourcePhrase}" как source drift: ${critic.driftSignalCount}/${critic.signalCount} строк ушли в омонимический или справочный спрос, строгий product-fit держат ${critic.strictFitSignalCount}.`;
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}
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if (critic.verdict === "mixed") {
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return `Source-group critic пометил Wordstat related-группу "${critic.sourcePhrase}" как mixed: в пачке есть drift-сигналы, поэтому related без строгого product-fit нельзя повышать в карту только по частотности.`;
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}
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return `Source-group critic не нашел групповой drift у Wordstat related-группы "${critic.sourcePhrase}".`;
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}
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function buildWordstatSourceGroupCritics(
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market: MarketEnrichmentContract,
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items: KeywordCleaningItem[]
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): Map<string, WordstatSourceGroupCritic> {
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const guard = buildKeywordCleaningFacetGuard(market);
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const groups = new Map<string, { sourcePhrase: string; items: KeywordCleaningItem[] }>();
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for (const item of items) {
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if (item.source !== "wordstat_related" || !item.sourcePhrase) {
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continue;
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}
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const normalizedSourcePhrase = normalizePhrase(item.sourcePhrase);
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const group = groups.get(normalizedSourcePhrase) ?? { items: [], sourcePhrase: item.sourcePhrase };
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group.items.push(item);
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groups.set(normalizedSourcePhrase, group);
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}
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const critics = new Map<string, WordstatSourceGroupCritic>();
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for (const [normalizedSourcePhrase, group] of groups.entries()) {
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const exactItems = group.items.filter((item) => item.frequency !== null && Boolean(item.wordstatResultId));
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const signalItems = exactItems.length >= SOURCE_GROUP_CRITIC_MIN_RESULTS ? exactItems : group.items;
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const driftItems = signalItems.filter((item) => hasSourceGroupRelatedDriftSignal(market, item.phrase));
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const strictFitItems = signalItems.filter(
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(item) => hasStrictRelatedProductFit(market, item.phrase, guard) && !hasSourceGroupRelatedDriftSignal(market, item.phrase)
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);
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const signalCount = signalItems.length;
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const driftShare = signalCount > 0 ? driftItems.length / signalCount : 0;
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const strictFitShare = signalCount > 0 ? strictFitItems.length / signalCount : 0;
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const sourceHasStrictFit = hasStrictRelatedProductFit(market, group.sourcePhrase, guard);
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const weakSource = sourceGroupLooksWeak(group.sourcePhrase, guard);
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const baseCritic = {
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driftExamples: driftItems.slice(0, 5).map((item) => item.phrase),
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driftSignalCount: driftItems.length,
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exactCount: exactItems.length,
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normalizedSourcePhrase,
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resultCount: group.items.length,
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signalCount,
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sourceHasStrictFit,
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sourceLooksWeak: weakSource,
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sourcePhrase: group.sourcePhrase,
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strictFitExamples: strictFitItems.slice(0, 5).map((item) => item.phrase),
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strictFitSignalCount: strictFitItems.length,
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verdict: getSourceGroupCriticVerdict({
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driftShare,
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driftSignalCount: driftItems.length,
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signalCount,
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sourceHasStrictFit,
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sourceLooksWeak: weakSource,
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strictFitShare,
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strictFitSignalCount: strictFitItems.length
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})
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};
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const critic: WordstatSourceGroupCritic = {
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...baseCritic,
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reason: buildWordstatSourceGroupCriticReason(baseCritic)
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};
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critics.set(normalizedSourcePhrase, critic);
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}
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return critics;
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}
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function getSourceGroupCriticEvidenceRef(critic: WordstatSourceGroupCritic) {
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return `backend:source-group-critic:${slugify(critic.sourcePhrase)}`;
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}
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function enforceWordstatSourceGroupCritic(
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market: MarketEnrichmentContract,
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items: KeywordCleaningItem[]
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): KeywordCleaningItem[] {
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const guard = buildKeywordCleaningFacetGuard(market);
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const critics = buildWordstatSourceGroupCritics(market, items);
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return items.map((item) => {
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if (item.source !== "wordstat_related" || !item.sourcePhrase) {
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return item;
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}
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const critic = critics.get(normalizePhrase(item.sourcePhrase));
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if (!critic || critic.verdict === "clean") {
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return item;
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}
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const selfHasDriftSignal = hasSourceGroupRelatedDriftSignal(market, item.phrase);
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const selfHasStrictFit = hasStrictRelatedProductFit(market, item.phrase, guard) && !selfHasDriftSignal;
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const blocker = critic.verdict === "source_drift" ? "source_group_related_drift" : "source_group_related_mixed";
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const evidenceRefs = unique([...item.evidenceRefs, getSourceGroupCriticEvidenceRef(critic)]);
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const blockers = unique([...(Array.isArray(item.blockers) ? item.blockers : []), blocker]);
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if (critic.verdict === "mixed") {
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if ((item.decision !== "use" && item.decision !== "support") || selfHasStrictFit) {
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return {
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...item,
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blockers,
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evidenceRefs
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};
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}
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return {
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...item,
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blockers,
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confidence: Math.min(item.confidence, 0.58),
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decision: "risky",
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evidenceRefs,
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reason: `${critic.reason} Backend guard понизил related без строгого product-fit в risky: mixed-группа требует ручной проверки.`
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};
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}
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if (selfHasStrictFit) {
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return {
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...item,
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blockers,
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confidence: Math.min(item.confidence, 0.58),
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decision: "risky",
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evidenceRefs,
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reason: `${critic.reason} Фраза сама держит product-fit, поэтому не удаляется, но не может попасть в approved lanes без ручной проверки source-группы.`
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};
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}
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return {
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...item,
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blockers,
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confidence: Math.max(item.confidence, 0.9),
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decision: "trash",
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evidenceRefs,
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reason: `${critic.reason} Backend guard отбросил фразу до keyword map: загрязненная source-группа не должна протаскивать омонимический related-спрос.`
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};
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});
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}
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function enforceKeywordCleaningNoiseGuard(items: KeywordCleaningItem[]): KeywordCleaningItem[] {
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return items.map((item) => {
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if (isOffContextRelatedNoisePhrase(item.normalizedPhrase)) {
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@ -756,7 +1032,10 @@ function enforceKeywordCleaningBackendGuards(
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items: KeywordCleaningItem[]
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): KeywordCleaningItem[] {
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return enforceKeywordCleaningNoiseGuard(
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promoteExactDemandItems(market, rescueExactTrashItems(market, enforceKeywordCleaningSemanticGuard(market, items)))
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enforceWordstatSourceGroupCritic(
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market,
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promoteExactDemandItems(market, rescueExactTrashItems(market, enforceKeywordCleaningSemanticGuard(market, items)))
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)
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);
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}
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||||
|
|
@ -1116,6 +1395,15 @@ function buildKeywordCleaningModelInput(contract: MarketEnrichmentContract): Key
|
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.sort((left, right) => right.score - left.score || left.index - right.index)
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.slice(0, KEYWORD_CLEANING_MODEL_TOP_RESULT_LIMIT)
|
||||
.map((item) => item.result);
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const modelSourceGroupCritics = [...buildWordstatSourceGroupCritics(contract, getBaseItems(contract)).values()]
|
||||
.filter((critic) => critic.verdict !== "clean")
|
||||
.sort(
|
||||
(left, right) =>
|
||||
(right.verdict === "source_drift" ? 1 : 0) - (left.verdict === "source_drift" ? 1 : 0) ||
|
||||
right.driftSignalCount - left.driftSignalCount ||
|
||||
right.resultCount - left.resultCount
|
||||
)
|
||||
.slice(0, SOURCE_GROUP_CRITIC_MODEL_LIMIT);
|
||||
|
||||
return {
|
||||
approvedAnchors: contract.anchorReview.wordstatQueue.slice(0, KEYWORD_CLEANING_MODEL_APPROVED_ANCHOR_LIMIT).map((anchor) => ({
|
||||
|
|
@ -1170,6 +1458,17 @@ function buildKeywordCleaningModelInput(contract: MarketEnrichmentContract): Key
|
|||
sourceClusterId: result.sourceClusterId,
|
||||
sourceClusterTitle: truncateTaskText(result.sourceClusterTitle),
|
||||
sourcePhrase: result.sourcePhrase
|
||||
})),
|
||||
sourceGroupCritics: modelSourceGroupCritics.map((critic) => ({
|
||||
driftExamples: critic.driftExamples.map((phrase) => truncateTaskText(phrase)),
|
||||
driftSignalCount: critic.driftSignalCount,
|
||||
exactCount: critic.exactCount,
|
||||
reason: truncateTaskText(critic.reason, 220),
|
||||
resultCount: critic.resultCount,
|
||||
sourcePhrase: truncateTaskText(critic.sourcePhrase),
|
||||
strictFitExamples: critic.strictFitExamples.map((phrase) => truncateTaskText(phrase)),
|
||||
strictFitSignalCount: critic.strictFitSignalCount,
|
||||
verdict: critic.verdict
|
||||
}))
|
||||
};
|
||||
}
|
||||
|
|
@ -1439,6 +1738,8 @@ function buildKeywordCleaningModelTask(
|
|||
broadFrequencyDoesNotOverrideSemanticFit: true,
|
||||
demoteRelatedWhenDominantFacetMissing: false,
|
||||
preserveApprovedAnchorFacets: true,
|
||||
quarantineNoisyRelatedGroups: true,
|
||||
sourceGroupDriftDoesNotEnterKeywordMap: true,
|
||||
riskyWhenNoPageBinding: false,
|
||||
trashWhenOffContext: true,
|
||||
useRequiresExactEvidence: true
|
||||
|
|
@ -1494,6 +1795,7 @@ function buildKeywordCleaningModelTask(
|
|||
"Отбрасывать бытовой AI/нейросетевой шум: онлайн, бесплатно, тексты, песни, фото, видео, чат, порно и похожие consumer-запросы не являются B2B SEO-кандидатами без source evidence.",
|
||||
"Образовательный спрос (курсы, обучение, тренинги, сертификаты) не отправлять в product keyword map, если Product Understanding/normalization не подтверждает образовательный offer сайта.",
|
||||
"Не повышать broad/head phrase до use/support, если Wordstat related потерял protected-смысл исходного якоря; глобальный доминантный термин проекта не должен запрещать отдельные подтверждённые ветки спроса.",
|
||||
"Проверять sourceGroupCritics после Wordstat: source_drift-группы не отправлять в keyword map, mixed-группы повышать только при строгом product/source fit у конкретной фразы.",
|
||||
"Не менять бизнес-вектор сайта; соседние рынки держать как article/backlog proposal.",
|
||||
"Не сохранять rewrite/apply decisions."
|
||||
],
|
||||
|
|
|
|||
|
|
@ -160,6 +160,15 @@ assert.ok(
|
|||
keywordCleaningSource.includes("getKeywordCleaningModelTopResultScore"),
|
||||
"Keyword cleaning model task must keep a slim ranked payload so AI Workspace does not fail with request entity too large."
|
||||
);
|
||||
assert.ok(
|
||||
keywordCleaningSource.includes("buildWordstatSourceGroupCritics") &&
|
||||
keywordCleaningSource.includes("enforceWordstatSourceGroupCritic") &&
|
||||
keywordCleaningSource.includes("source_group_related_drift") &&
|
||||
keywordCleaningSource.includes("sourceGroupCritics") &&
|
||||
keywordCleaningSource.includes("quarantineNoisyRelatedGroups") &&
|
||||
keywordCleaningSource.includes("sourceGroupDriftDoesNotEnterKeywordMap"),
|
||||
"Keyword cleaning must run a source-group/related-fit critic after Wordstat so homonym related batches are quarantined before keyword map."
|
||||
);
|
||||
assert.ok(
|
||||
modelProviderRegistrySource.includes('"seo.market_frontier_discovery"'),
|
||||
"Model provider registry must expose seo.market_frontier_discovery as a runnable task type."
|
||||
|
|
|
|||
Loading…
Reference in New Issue