_{Canva Design}

My project today is for calculating similarity or you can say it is for detecting plagiarism. The method will be something like this: there will be two files in it, these files will be compared, and the plagiarism of both of them will be detected.

Key Points:

• This will remove punctuation and convert the text to lower case, eliminating common words such as in the end and etc. It will only focus on words that are meaningful.
• It will compare two files in the app, process their text, and then check for similarity based on a word sequence.
• This will calculate the percentage of text similarity, how many words are common in both files, and what percentage.
• It is designed in such a way that it will check the similarity of the text and see if the other file is not given in the rewritten version and will focus on the meaningful full words and ignore all the other common phrases.
• In this, we have to take two text files, both of these text files will contain our text and we will compare both of them.

Explanation

Now let's move on to the functionalities of our project, and how each function is working.

Stop Words:

In this entire set, we have included words that are very common and that we want to exclude from our text. All these words do not help us determine whether two files are similar or have been rewritten. We will exclude them and check for duplication based on the specific words that are present.

Preprocessing Text:

Here, using this remove_if and ::ispunct, we remove the punctuations like periods, commas, etc.

Additionally, using transform and ::tolower, converts characters to lowercase and ensures that it is case-insensitive.

Splitting & Removing Stop Words:

The text is split into individual words using a stringstream. As each word comes out, the code then checks if it is a stop word. If it is not a stop word, it adds it to the words vector.

Read File Contents:

This function is used to read a file. It reads the entire content. If the file is not open, then it shows an error message.

Calculate Similarity:

Two lists of words are converted into one set unordered_set to eliminate duplication. It counts the common words between these two sets by checking them.

When similarity is checked as a percentage, it does so by taking into account the unique words between the two sets. Finally, this function shares the list of matching words between these two sets and reports the percentage.

Main Function:

First, the file input is taken from the user, the user will put the names of both the files there, after which this main function will read these two files and store them in a string, then the result of both of them will be processed, there will be pre-processing in which punctuation will be removed and it will be converted to lower case, then after that the stop words present in both will be eliminated and later the similarity words in it will be calculated and their percentage and their list will be shown in the result.

C++ Code File

Output

• 01.
  First of all, we will input the same data in both the two text files we have and check both of them by running this program. Then what result do we get below?