Cosine Similarity Calculator, by Tyler Newton (Applied Software Design, LLC.)
If you find this calculator useful, (i.e. it helps you) please make a donation of any amount towards our efforts.
This Cosine Similarity Calculator will teach you how to calculate the Cosine Similarity (a.k.a. how to calculate the Cosine Measure)
of two vectors. Useful for both math homework and data mining.
The Cosine Similarity of two vectors is an arbitrary mathematical measure of how
similar two vectors are on a scale of [0, 1]. 1 being that the vectors are either
identical, or that their values differ by a constant factor.
The Cosine Similarity of two vectors (d1 and d2) is defined as:
cos( d1, d2 ) = dot(d1,d2) / ||d1|| ||d2||
Where dot(d1,d2) = d1[0]*d2[0] + d1[1]*d2[1] ...
And Where ||d1|| = sqrt(d1[0]^2 + d1[1]^2 ...)
(Additional Info For Data Miners: The Centroid Similarity Measure is simply the Cosine Measure of your clustering output.
e.g. After clustering some data, if you only have two centroids, to get the Centroid Similarity Measure, you just
take the Cosine Measure of the resultant vectors. If you have k centroids though such that k > 2 (and this formula works
for k=2 as well), then it is the Summation From i=1 to K(Summation From j=1 to K (Cosine Similarity(Ci,Cj))).
This is a Cosine Similarity Calculator. There is currently no data validation. Make sure your vectors are of equal
length, numeric in type, and with each value separated by a single space. For example ~> "1 2 3" (without the quote marks)
would be a valid input: