How to Install and Uninstall libstemmer0d Package on Kali Linux

Last updated: December 25,2024

1. Install "libstemmer0d" package

This guide covers the steps necessary to install libstemmer0d on Kali Linux


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                libstemmer0d
            
                    
    
    Copied

2. Uninstall "libstemmer0d" package

In this section, we are going to explain the necessary steps to uninstall libstemmer0d on Kali Linux:


    
        
            $
        

        
            
                sudo apt remove
            
                        
                libstemmer0d
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the libstemmer0d package on Kali Linux

Package: libstemmer0d
Source: snowball (2.2.0-4)
Version: 2.2.0-4+b1
Installed-Size: 819
Maintainer: Stefano Rivera
Architecture: amd64
Depends: libc6 (>= 2.4)
Size: 118880
SHA256: 18ccf7ab91e36293d4f3e0d1ce08b98877ad0408a09f38de484d4d4aa0cdfadd
SHA1: 1ee5e080067cb1bccb9672e3b14cd56ba66c46f9
MD5sum: 9818fb543d0e221913d33a50c8a9ff38
Description: Snowball stemming algorithms for use in Information Retrieval
Snowball provides access to efficient algorithms for calculating a
"stemmed" form of a word. This is a form with most of the common
morphological endings removed; hopefully representing a common
linguistic base form. This is most useful in building search engines
and information retrieval software; for example, a search with stemming
enabled should be able to find a document containing "cycling" given the
query "cycles".
.
Snowball provides algorithms for several (mainly European) languages.
It also provides access to the classic Porter stemming algorithm for
English: although this has been superseded by an improved algorithm, the
original algorithm may be of interest to information retrieval
researchers wishing to reproduce results of earlier experiments.
Description-md5:
Multi-Arch: same
Homepage: https://snowballstem.org/
Tag: role::shared-lib
Section: libs
Priority: optional
Filename: pool/main/s/snowball/libstemmer0d_2.2.0-4+b1_amd64.deb