делаю TF IDF ранжиорвание

#include <algorithm>
#include <iostream>
#include <set>
#include <string>
#include <utility>
#include <vector>
#include <map>

using namespace std;

const int MAX_RESULT_DOCUMENT_COUNT = 5;

string ReadLine() {
    string s;
    getline(cin, s);
    return s;
}

int ReadLineWithNumber() {
    int result = 0;
    cin >> result;
    ReadLine();
    return result;
}

vector<string> SplitIntoWords(const string& text) {
    vector<string> words;
    string word;
    for (const char c : text) {
        if (c == ' ') {
            if (!word.empty()) {
                words.push_back(word);
                word.clear();
            }
        } else {
            word += c;
        }
    }
    if (!word.empty()) {
        words.push_back(word);
    }

    return words;
}

struct Document {
    int id;
    double relevance; //
};

class SearchServer {
public:
    void SetStopWords(const string& text) {
        for (const string& word : SplitIntoWords(text)) {
            stop_words_.insert(word);
        }
    }

    void AddDocument(int document_id, const string& document) {
        const vector<pair<string, double>> words = SplitIntoWordsNoStopWithTF(document);
        for (auto wrd:words){
           word_to_document_freqs_[wrd.first].insert({document_id, wrd.second});

        }
    //////////// отображаем че там попало /////
      /*  for (auto word_key: word_to_document_freqs_)
        {
            cout << word_key.first<<":";
            for (auto id_tf: word_to_document_freqs_[word_key.first])
            {
              cout << id_tf.first << "--" << id_tf.second<<endl;
            }
        }*/
    ///////////

    }

    vector<Document> FindTopDocuments(const string& raw_query) const {
        const QueryContent query_words = ParseQuery(raw_query);
        auto matched_documents = FindAllDocuments(query_words);

        sort(matched_documents.begin(), matched_documents.end(),
             [](const Document& lhs, const Document& rhs) {
                 return lhs.relevance > rhs.relevance;
             });
        if (matched_documents.size() > MAX_RESULT_DOCUMENT_COUNT) {
            matched_documents.resize(MAX_RESULT_DOCUMENT_COUNT);
        }
        return matched_documents;
    }

private:
    //map<string, set<int>>  word_to_documents_;
    map<string, map<int, double>> word_to_document_freqs_;
    int document_count_ = 0;

    struct QueryContent {
        set<string> pluswords;
        set<string> minuswords;
    };

    set<string> stop_words_;

    bool IsStopWord(const string& word) const {
        return stop_words_.count(word) > 0;
    }

    vector<string> SplitIntoWordsNoStop(const string& text) const {
        vector<string> words;
        for (const string& word : SplitIntoWords(text)) {
            if (!IsStopWord(word)) {
                words.push_back(word);
            }
        }
        return words;
    }
    //////////вычисление числа одинаковых слов в векторе///
    int WordsCountInvector(string word, vector<string> vctrwords)
    {
    int count=0;
        for (string wrd:vctrwords)
        {
        if (word==wrd) ++count;
        }
        return count;
    }
    /////////////////
    ////// разбивка на слова с вычислением TF
    vector <pair<string, double>> SplitIntoWordsNoStopWithTF(const string& text) /*const*/ {
    vector <pair<string, double>> words_n_TF;
    pair<string, double> temp;
    vector<string> rawwords = SplitIntoWordsNoStop(text);
    int vsize = rawwords.size();
        for (string wrd:rawwords) {
        temp.first=wrd;
        temp.second=1.0*WordsCountInvector(wrd,rawwords)/vsize;
        words_n_TF.push_back(temp);
    }
    return words_n_TF;
    }
    ///////////
    QueryContent ParseQuery(const string& text) const {
        QueryContent query_words;
        for (const string& word : SplitIntoWordsNoStop(text)) {
            if (word[0]!='-') query_words.pluswords.insert(word);
            else {
                query_words.minuswords.insert(word.substr(1));
             }
        }
        return query_words;
    }

    vector<Document> FindAllDocuments(const QueryContent query_words) const {
        map <int,double> document_to_relevance;  //
        vector<Document> matched_documents;
        for (const auto& qwr_wrd : query_words.pluswords)
        {
            if (word_to_document_freqs_.count(qwr_wrd))
            {
                for (auto id_tf : word_to_document_freqs_.at(qwr_wrd))
                {
                    document_to_relevance[id_tf.first]=id_tf.second;
                }
            }
        }
        for (const auto& qwr_mwrd : query_words.minuswords)
        {
            if (word_to_document_freqs_.count(qwr_mwrd))
            {
                for (auto id_tf:word_to_document_freqs_.at(qwr_mwrd))
                {
                    document_to_relevance.erase(id_tf.first);
                }
            }
        }
        for (const auto& dctorlv:document_to_relevance)
        {
           matched_documents.push_back({dctorlv.first,dctorlv.second});
        }
        cout << "--==="<< matched_documents.size() << "===--" << endl;
        return matched_documents;
    }
    };

SearchServer CreateSearchServer() {
    SearchServer search_server;
    search_server.SetStopWords(ReadLine());

    const int document_count = ReadLineWithNumber();
    for (int document_id = 0; document_id < document_count; ++document_id) {
        search_server.AddDocument(document_id, ReadLine());
    }

    return search_server;
}

int main() {
    const SearchServer search_server = CreateSearchServer();

    const string query = ReadLine();
    for (const auto& [document_id, relevance] : search_server.FindTopDocuments(query)) {
        cout << "{ document_id = "s << document_id << ", "
             << "relevance = "s << relevance << " }"s << endl;
    }
}