func SendSuggestion(suggestion model.Suggestion, c *model.WsContext) {
if suggestion.Recommendation.Genesis == c.UserId {
return
}
if _, in := SentSuggestions[c.UserId]; in {
for _, sentSuggestion := range SentSuggestions[c.UserId] {
distance := matchr.Levenshtein(suggestion.Recommendation.Text, sentSuggestion.Recommendation.Text)
if distance < 10 {
return
}
}
} else {
SentSuggestions[c.UserId] = make([]model.Suggestion, 0)
}
log.Info("Sending suggestion to user %v", c.UserId)
SentSuggestions[c.UserId] = append(SentSuggestions[c.UserId], suggestion)
SentSuggestions[suggestion.Recommendation.Genesis] = append(SentSuggestions[suggestion.Recommendation.Genesis], suggestion)
c.SendI(suggestion)
}
//fuzzyMap uses a word-similarity algorithm to match a value to its dictionary key, then assigns it the dictionary value
func fuzzyMap(datum string, mappings []datasources.Setting) string {
var distances []float64
result := ""
for _, mapping := range mappings {
d := matchr.Levenshtein(datum, mapping.Label)
distances = append(distances, float64(d))
}
minDistance, err := stats.Min(distances)
if err != nil {
log.Fatal("Error finding minimum: ", err)
}
for i, distance := range distances {
if int(minDistance) == int(distance) {
result = mappings[i].Value
break
}
}
return result
}
