JWS -- Java WordNet similarity is an open-source project developed by David hope of the University of Sussex to calculate semantic similarity between Java and WordNet.It implements many classical semantic similarityAlgorithm. It is an open-source
Similarity Calculation Based on grain Coefficient
// This program ignores the preference value and calculates the similarity based on the grain coefficient. // This algorithm is based on the grain coefficient. // This value is also called the
Evaluation of similarity recommendation algorithm based on Euclidean distance Definition
/** This program evaluates the similarity defined based on Euclidean distance **/package byuser; import java. io. file; import org. apache. mahout. cf. taste.
The Java string similarity algorithm is described in the example. Share to everyone for your reference. The implementation methods are as follows:
Copy Code code as follows:
public class Levenshtein {
private int Compare (string str,
TurnIt's not difficult to understand, but it's practical.The core formula is the following:(1)1. Introduction of Baidu Encyclopedia:Levenshtein distance, also known as the editing distance, refers to the minimum number of edit operations required
The previous example of massive data similarity calculation simhash and Hamming distance we introduced the principle of simhash, we should feel the charm of the algorithm. But as the business grows, so does simhash data, and if the day 100w,10 1000w.
Original: http://www.open-open.com/code/view/1448334323079ImportJava.awt.image.BufferedImage;ImportJava.io.File;ImportJavax.imageio.ImageIO;/*** Compare the similarity of two pictures *@authorGuihua **/ Public classBmploader {//change into binary
Public class test {/*** we define the similarity between two strings as the cost of converting a string into another string (the conversion method may not be unique ), the higher the conversion cost, the lower the similarity between the two strings.
This article illustrates a Java comparison of two picture similarity methods. Share to everyone for your reference. Specifically as follows:
Summary:
Importjava.awt.image.BufferedImage;Importjava.io.File;Importjavax.imageio.ImageIO;/*** Compare
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