func main() {
// Definition of Command-Line Params
param_data_file := flag.String("f", "", "path to a file containing News-titles")
// param_interactively := flag.Bool("i", false, "run interactively")
param_purge := flag.Bool("purge", false, "reinitialize the database, purging all existing data")
param_cosine := flag.Bool("cosine", false, "calculate CosineSimilarity instead of ngram-clusering")
param_title := flag.String("title", "", "print out similar news-titles")
param_count := flag.Int("n", 3, "how many similar news titles should be printed?")
flag.Parse()
data.InitializeDatabase("root", "")
data.Connect(database_name, *param_purge)
if len(*param_data_file) > 0 {
data.ParseFile(*param_data_file)
}
if !*param_cosine {
if len(*param_title) > 0 {
for _, match := range bestmatches.GetBestMatches(*param_title, *param_count) {
fmt.Println(match)
}
}
}
if *param_cosine {
titleCount := data.GetCountOfTitles()
// 6. Prepare to calculate distances
var title_1 int
var title_2 int
fmt.Printf("Enter number for first title (%d): ", titleCount)
fmt.Scanln(&title_1)
fmt.Printf("Enter number for second title (%d): ", titleCount)
fmt.Scanln(&title_2)
data_1 := data.GetTrigramsByTitle(data.GetNewsTitle(title_1))
data_2 := data.GetTrigramsByTitle(data.GetNewsTitle(title_2))
fmt.Printf("+-----------------------------+\n"+
"| Cosine similarity: %f |\n"+
"+-----------------------------+",
ai.CosineSimilarity(ai.NormalizeTwoVectors(data_1, data_2)))
}
}
// returns n=count titles matching to the title
func GetBestMatches(title string, count int) []string {
var trigram_matches []int
// first calculate ngrams of the search string
for _, trigram := range ngram.BuildNGram(title, 3) {
for _, match := range data.GetIdsOfTrigram(trigram) {
trigram_matches = append(trigram_matches, match)
}
}
// TODO: now get the *count* most frequent news ids
frequencies := map[int]int{}
for _, id := range trigram_matches {
_, contains := frequencies[id]
if contains {
frequencies[id] += 1
} else {
frequencies[id] = 1
}
}
// now sort according to the count
sorted := SortByFrequency(trigram_matches, frequencies)
return_val := []int{}
for i := 0; i <= count; i += 1 {
return_val = append(return_val, sorted[i])
}
// get the according titles
titles := []string{}
for id := range return_val {
titles = append(titles, data.GetNewsTitle(id))
}
return titles
}
