The formula for calculating the City Block (Manhattan) Distance is |x2 - x1| + |y2 - y1|. First, I will provide a brief example the City Block (Manhattan) Distance. These types of similarity distance measurements are City Block (Manhattan) Distance, Euclidean Distance, and the Cosine Similarity and Cosine Distance. There are three types of similarity distance measurements that I will be discussing. It really leads to the conclusion, of “who do we believe”? That is why I chose this particular topic to write about because I found that it was interesting that in using Python, I was able to calculate the similarity and dissimilarity between text documents.īefore getting further into the article, I think it would be important to discuss the three types of similarity distance measurements that I came across during my research.
#Similarity series
They were reporting on the same story, but it was almost like they were reporting on a completely different series of events. Also, of particular interest, was the dissimilarity when comparing one news organization to another. This has only become a recent interest of mine within the past five to seven years, but one of the strangest things that I began to realize was the similarity of various news articles from different organizations. The main reason that I like to read about world news and events, is that I simply like to stay informed. I’m not quite sure if this would be considered a hobby, but one of my favorite things to do is read about world news and events.
Using Python to Calculate Similarity Distance Measurement for Text Analysis
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