83 lines
2.0 KiB
Go
83 lines
2.0 KiB
Go
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package knowledge
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import (
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"sort"
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"strings"
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)
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// SelectBestSearchKeywords pools research map, graph, product, and optional hints,
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// then returns the most intent-relevant phrases for Search API (not UI display order).
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func SelectBestSearchKeywords(explicit, saved []string, in PatrolTagInput, nodes []Node, limit int) []string {
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if limit <= 0 {
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limit = MaxScanPatrolKeywords
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}
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profile := BuildIntentProfile(in)
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candidates := BuildPatrolCandidates(in, nodes)
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for i, tag := range NormalizePatrolKeywordList(explicit) {
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addPatrolCandidate(&candidates, tag, 156-i, "掃描指定", patrolIntentRelevance)
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}
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for i, tag := range NormalizePatrolKeywordList(saved) {
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if containsNormalizedTag(explicit, tag) {
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continue
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}
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addPatrolCandidate(&candidates, tag, 88-i, "研究地圖儲存", patrolIntentRelevance)
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}
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type ranked struct {
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tag string
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score int
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}
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scored := make([]ranked, 0, len(candidates))
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seen := map[string]struct{}{}
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for _, item := range selectTopPatrolCandidates(candidates, len(candidates)+32) {
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tag := strings.TrimSpace(item.Tag)
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if tag == "" {
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continue
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}
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key := patrolTagDedupeKey(tag)
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if _, ok := seen[key]; ok {
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continue
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}
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seen[key] = struct{}{}
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if IsTangentialToIntent(tag, profile) {
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continue
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}
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intent := ScoreIntentSimilarity(tag, profile)
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if intent < 8 && item.Score < 65 {
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continue
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}
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final := (item.Score*2 + intent*4) / 6
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if final <= 0 {
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continue
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}
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scored = append(scored, ranked{tag: tag, score: final})
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}
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sort.SliceStable(scored, func(i, j int) bool {
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if scored[i].score == scored[j].score {
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return scored[i].tag < scored[j].tag
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}
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return scored[i].score > scored[j].score
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})
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out := make([]string, 0, limit)
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for _, item := range scored {
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out = append(out, item.tag)
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if len(out) >= limit {
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break
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}
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}
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return out
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}
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func containsNormalizedTag(items []string, target string) bool {
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targetKey := patrolTagDedupeKey(target)
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for _, item := range items {
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if patrolTagDedupeKey(item) == targetKey {
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return true
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}
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}
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return false
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}
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