Count of words that are present in all the given sentences

Given n sentences. The task is to count the number of words that appear in all of these sentences. Note that every word consists of only lowercase English alphabets.

Examples:

Input: arr[] = {
“there is a cow”,
“cow is our mother”,
“cow gives us milk and milk is sweet”,
“there is a boy who loves cow”}
Output: 2
Only the words “is” and “cow” appear in all of the sentences.



Input: arr[] = {
“abc aac abcd ccc”,
“ac aa abc cca”,
“abca aaac abcd ccc”}
Output: 0

Naive Approach: The naive approach is to take every word of the first sentence and compare it with rest of the lines if it is also present in all lines then increment the count.

Efficient Approach: For all the words of the first sentence, we can check if it is also present in all the other sentences in constant time by using a map. Store all the words of the first sentence in a map and check how many of these stored words are present in all of the other sentences.

C++

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// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;
  
// Function to return the count of common words
// in all the sentences
int commonWords(vector<string> S)
{
    int m, n, i, j;
  
    // To store separate words
    string str;
  
    // It will be used to check if a word is present
    // in a particuler string
    unordered_map<string, bool> has;
  
    // To store all the words of first string
    vector<pair<string, bool> > ans;
  
    pair<string, bool> tmp;
  
    // m will store number of strings in given vector
    m = S.size();
  
    i = 0;
  
    // Extract all words of first string and store it in ans
    while (i < S[0].size()) {
        str = "";
        while (i < S[0].size() && S[0][i] != ' ') {
            str += S[0][i];
            i++;
        }
  
        // Increase i to get at starting index
        // of the next word
        i++;
  
        // If str is not empty store it in map
        if (str != "") {
            tmp = make_pair(str, true);
            ans.push_back(tmp);
        }
    }
  
    // Start from 2nd line check if any word of
    // the first string did not match with
    // some word in the current line
    for (j = 1; j < m; j++) {
        has.clear();
        i = 0;
  
        while (i < S[j].size()) {
            str = "";
            while (i < S[j].size() && S[j][i] != ' ') {
                str += S[j][i];
                i++;
            }
            i++;
            if (str != "") {
                has[str] = true;
            }
        }
  
        // Check all words of this vector
        // if it is not present in current line
        // make it false
        for (int k = 0; k < ans.size(); k++) {
            if (ans[k].second != false
                && has[ans[k].first] == false) {
                ans[k].second = false;
            }
  
            // This line is used to consider only distinct words
            else if (ans[k].second != false
                     && has[ans[k].first] == true) {
                has[ans[k].first] = false;
            }
        }
    }
  
    // This function will print
    // the count of common words
    int cnt = 0;
  
    // If current word appears in all the sentences
    for (int k = 0; k < ans.size(); k++) {
        if (ans[k].second == true)
            cnt++;
    }
  
    return cnt;
}
  
// Driver code
int main()
{
    vector<string> S;
    S.push_back("there is a cow");
    S.push_back("cow is our mother");
    S.push_back("cow gives us milk and milk is sweet");
    S.push_back("there is a boy who loves cow");
  
    cout << commonWords(S);
  
    return 0;
}

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Java














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// Java implementation of the approach  


import java.util.HashMap; 


  


class GFG 


{ 


  


    // Function to return the count of  


    // common words in all the sentences 


    static int commonWords(String[] s)  


    { 


        int m, i, j; 


  


        // To store separate words 


        String str; 


  


        // It will be used to check if a word  


        // is present in a particuler string 


        HashMap<String, Boolean> has = new HashMap<>(); 


  


        // To store all the words of first string 


        String[] ans1 = new String[100]; 


        boolean[] ans2 = new boolean[100]; 


        int track = 0; 


  


        // m will store number of strings  


        // in given vector 


        m = s.length; 


        i = 0; 


  


        // Extract all words of first string  


        // and store it in ans 


        while (i < s[0].length())  


        { 


            str = ""; 


            while (i < s[0].length() && 


                       s[0].charAt(i) != ' ') 


            { 


                str += s[0].charAt(i); 


                i++; 


            } 


  


            // Increase i to get at starting index 


            // of the next word 


            i++; 


  


            // If str is not empty store it in map 


            if (str.compareTo("") != 0) 


            { 


                ans1[track] = str; 


                ans2[track] = true; 


                track++; 


            } 


        } 


  


        // Start from 2nd line check if any word of 


        // the first string did not match with 


        // some word in the current line 


        for (j = 1; j < m; j++) 


        { 


            has.clear(); 


            i = 0; 


            while (i < s[j].length()) 


            { 


                str = ""; 


                while (i < s[j].length() && 


                           s[j].charAt(i) != ' ') 


                { 


                    str += s[j].charAt(i); 


                    i++; 


                } 


  


                i++; 


                if (str.compareTo("") != 0) 


                    has.put(str, true); 


            } 


  


            // Check all words of this vector 


            // if it is not present in current line 


            // make it false 


            for (int k = 0; k < track; k++) 


            { 


                // System.out.println(has.get(ans1[k])); 


                if (ans2[k] != false &&  


                    !has.containsKey(ans1[k])) 


                    ans2[k] = false; 


  


                // This line is used to consider 


                // only distinct words 


                else if (ans2[k] != false &&  


                         has.containsKey(ans1[k]) &&  


                         has.get(ans1[k]) == true) 


                    has.put(ans1[k], false); 


            } 


        } 


  


        // This function will print 


        // the count of common words 


        int cnt = 0; 


  


        // If current word appears  


        // in all the sentences 


        for (int k = 0; k < track; k++) 


            if (ans2[k] == true) 


                cnt++; 


  


        return cnt; 


    } 


  


    // Driver Code 


    public static void main(String[] args)  


    { 


        String[] s = { "there is a cow", "cow is our mother", 


                       "cow gives us milk and milk is sweet", 


                       "there is a boy who loves cow" }; 


  


        System.out.println(commonWords(s)); 


    } 


} 


  


// This code is contributed by 


// sanjeev2552 



















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Python3














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# Python3 implementation of the approach  


from collections import defaultdict 


  


# Function to return the count of  


# common words in all the sentences  


def commonWords(S):  


  


    # It will be used to check if a word  


    # is present in a particuler string  


    has = defaultdict(lambda:False)  


  


    # To store all the words of first string  


    ans = []  


  


    # m will store number of strings  


    # in given vector  


    m = len(S)  


  


    i = 0


      


    # Extract all words of first string  


    # and store it in ans  


    while i < len(S[0]):  


        string = ""  


        while i < len(S[0]) and S[0][i] != ' ':  


            string += S[0][i]  


            i += 1


  


        # Increase i to get at starting  


        # index of the next word  


        i += 1


  


        # If str is not empty store it in map  


        if string != "":  


            ans.append([string, True])  


  


    # Start from 2nd line check if any word  


    # of the first string did not match with  


    # some word in the current line  


    for j in range(1, m): 


        has.clear()  


        i = 0


  


        while i < len(S[j]):  


            string = ""  


            while i < len(S[j]) and S[j][i] != ' ':  


                string += S[j][i]  


                i += 1


              


            i += 1


            if string != "":  


                has[string] = True


          


        # Check all words of this vector  


        # if it is not present in current  


        # line make it false  


        for k in range(0, len(ans)):  


            if (ans[k][1] != False and


                has[ans[k][0]] == False):  


                ans[k][1] = False


              


            # This line is used to consider  


            # only distinct words  


            elif (ans[k][1] != False


                and has[ans[k][0]] == True):  


                has[ans[k][0]] = False


  


    # This function will print  


    # the count of common words  


    cnt = 0


  


    # If current word appears in all 


    # the sentences  


    for k in range(0, len(ans)):  


        if ans[k][1] == True:  


            cnt += 1


  


    return cnt  


  


# Driver code  


if __name__ == "__main__": 


  


    S = []  


    S.append("there is a cow")  


    S.append("cow is our mother")  


    S.append("cow gives us milk and milk is sweet")  


    S.append("there is a boy who loves cow")  


  


    print(commonWords(S))  


  


# This code is contributed by Rituraj Jain  



















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Output:


2







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