Text Similarity

Text Similarity Calculator

A Python implementation of cosine similarity to measure how similar two texts are to each other.

What is Cosine Similarity?

Cosine similarity is a metric used to determine how similar two documents are regardless of their size. Mathematically, it measures the cosine of the angle between two vectors in a multi-dimensional space.

The mathematical formula is:

Cosine Similarity = (A·B) / (||A|| × ||B||)

Where:

• A·B is the dot product of vectors A and B
• ||A|| and ||B|| are the magnitudes (or norms) of vectors A and B

How This Program Works

1. Input: The program takes two text strings as input.

2. Text Processing:

   • Converts the texts to lowercase
   • Splits them into individual words
   • Creates frequency matrices for each word in both texts

3. Vector Creation:

   • Each unique word becomes a dimension in our vector space
   • The frequency of each word becomes its magnitude in that dimension

4. Similarity Calculation:

   • Calculates the dot product of the two word frequency vectors
   • Calculates the magnitudes of both vectors
   • Computes the cosine similarity using the formula above

5. Output: Returns a similarity score between 0 and 1

   • 1 means the texts are identical
   • 0 means they have nothing in common
   • Values in between indicate partial similarity

Usage

Run the program and input two texts when prompted:

python cosine.py

Example:

Text 1: Julie loves me more than Linda loves me
Text 2: Jane likes me more than Julie loves me

The program will display:

• The words and their frequencies in each text
• The dot product calculation
• The final cosine similarity score