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|
package search
import (
"cmp"
"searchEngine/core/analyzer"
"searchEngine/core/index"
"searchEngine/core/scoring"
"slices"
)
type Result struct {
DocID int
Score float64
}
func Search(idx *index.InvertedIndex, query string) []string {
tokenizedQuery := analyzer.ProcessText(query)
if len(tokenizedQuery) == 0 {
return nil
}
idx.Mu.RLock()
defer idx.Mu.RUnlock()
totalDocs := len(idx.DocNames)
docMatchCounts := make(map[int]int)
scores := make(map[int]float64)
uniqueMap := make(map[string]bool)
var uniqueTokens []string
for _, token := range tokenizedQuery {
if !uniqueMap[token] {
uniqueMap[token] = true
uniqueTokens = append(uniqueTokens, token)
}
}
for _, token := range tokenizedQuery {
postings, exists := idx.Data[token]
if !exists {
return nil
}
docFrequency := len(postings)
idf := scoring.CalculateIDF(totalDocs, docFrequency)
for _, p := range postings {
docMatchCounts[p.DocId]++
termScore := scoring.ScoreTFIDF(p, idf)
scores[p.DocId] += termScore
}
}
var results []Result
for docID, count := range docMatchCounts {
if count == len(uniqueTokens) {
results = append(results, Result{DocID: docID, Score: scores[docID]})
}
}
slices.SortFunc(results, func(a, b Result) int {
return cmp.Compare(b.Score, a.Score)
})
var titles []string
for _, res := range results {
if title, exists := idx.DocNames[res.DocID]; exists {
titles = append(titles, title)
}
}
return titles
}
|
