如何在C++中进行情感识别和情感分析？

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#include <iostream>

#include <map>

#include <vector>

using namespace std;

map<string, double> trainNaiveBayesModel(const vector<vector<string>>& trainingData, const vector<string>& labels) {

    map<string, double> model;

    int numPositiveWords = 0, numNegativeWords = 0;

    map<string, int> positiveWordCount, negativeWordCount;

    for (int i = 0; i < trainingData.size(); ++i) {

        const auto& document = trainingData[i];

        const auto& label = labels[i];

        for (const auto& word : document) {

            if (label == "positive") {

                positiveWordCount[word]++;

                numPositiveWords++;

            } else if (label == "negative") {

                negativeWordCount[word]++;

                numNegativeWords++;

            }

        }

    }

    for (const auto& entry : positiveWordCount) {

        const auto& word = entry.first;

        const auto& count = entry.second;

        model[word] = (count + 1) / double(numPositiveWords + positiveWordCount.size());

    }

    for (const auto& entry : negativeWordCount) {

        const auto& word = entry.first;

        const auto& count = entry.second;

        model[word] = (count + 1) / double(numNegativeWords + negativeWordCount.size());

    }

    return model;

}

string classifyDocument(const vector<string>& document, const map<string, double>& model) {

    double positiveProbability = 0, negativeProbability = 0;

    for (const auto& word : document) {

        if (model.count(word) > 0) {

            positiveProbability += log(model.at(word));

            negativeProbability += log(1 - model.at(word));

        }

    }

    if (positiveProbability > negativeProbability) {

        return "positive";

    } else {

        return "negative";

    }

}

int main() {

    vector<vector<string>> trainingData = {{"I", "love", "this", "movie"},

                                           {"I", "hate", "this", "movie"},

                                           {"It", "is", "amazing"},

                                           {"It", "is", "terrible"}};

    vector<string> labels = {"positive", "negative", "positive", "negative"};

    map<string, double> model = trainNaiveBayesModel(trainingData, labels);

    vector<string> document = {"I", "love", "this", "movie"};

    string sentiment = classifyDocument(document, model);

    cout << "Sentiment of the document: " << sentiment << endl;

    return 0;

}

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