Hash is a term with various meanings in different industries. In the context of text analytics, a hash is a value that is generated by applying a hashing algorithm to a piece of text. This value can be used to identify or compare texts.
There are many different hashing algorithms, and each will produce a different hash value for the same input. Some of the more common algorithms include MD5, SHA-1, and SHA-256.
Importance of Performing Hash
- Determining whether two pieces of text are identical: Hashes can be used to quickly compare two pieces of text to see if they are identical. This can be useful, for example, when checking for plagiarism.
- Identifying duplicate texts: Hashes can be used to identify duplicate texts. This can be useful, for example, when trying to find all instances of a particular text.
- Creating a fingerprint for a text: Hashes can be used to create a “fingerprint” for a text. This fingerprint can be used to identify the text, even if it has been modified slightly.
Disadvantages of Performing Hash
Hashes are not foolproof: Two different pieces of text can generate the same hash value. This is called a “collision.” While collisions are rare, they do happen.
Hashes can be time-consuming to generate: Depending on the size of the text and the hashing algorithm being used, it can take a significant amount of time to generate a hash.
Tools used to Perform Hash
Many different tools can be used to generate hashes for text analytics purposes. Some of these tools are listed below:
- John the Ripper