The reverse process of stemming

reverse stemming python
process of nlp normalizes words into base or root form.
porter stemmer online
stemming api
stemming algorithm python
lancaster stemmer python

I use a lucene snowball analyzer to perform stemming . The results are not meaningful words . I referred this question .

One of the solution is to use a database that contains a map between the stemmed version of the word to one stable version of the word . (Example from communiti to community no matter what the base was for communti (communities / or some other word))

I want to know if there is a database which performs such a function.

It is theoretically impossible to recover a specific word from a stem, since one stem can be common to many words. One possibility, depending on your application, would be to build a database of stems each mapped to an array of several words. But you would then need to predict which one of those words is appropriate given a stem to re-convert.

As a very naive solution to this problem, if you know the word tags, you could try storing words with the tags in your database:

   NN:  runner
   VBG: running
   VBZ: runs

Then, given the stem "run" and the tag "NN", you could determine that "runner" is the most probable word in that context. Of course, that solution is far from perfect. Notably, you'd need to handle the fact that the same word form might be tagged differently in different contexts. But remember that any attempt to solve this problem will be, at best, an approximation.

Edit: from the comments below, it looks like you probably want to use lemmatization instead of stemming. Here's how to get the lemmas of words using the Stanford Core NLP tools:

import java.util.*;

import edu.stanford.nlp.pipeline.*;
import edu.stanford.nlp.ling.*;
import edu.stanford.nlp.ling.CoreAnnotations.*;

Properties props = new Properties();

props.put("annotators", "tokenize, ssplit, pos, lemma");
pipeline = new StanfordCoreNLP(props, false);
String text = "Hello, world!";
Annotation document = pipeline.process(text);

for(CoreMap sentence: document.get(SentencesAnnotation.class)) {
    for(CoreLabel token: sentence.get(TokensAnnotation.class)) {
        String word = token.get(TextAnnotation.class);
        String lemma = token.get(LemmaAnnotation.class);

java - The reverse process of stemming, It is theoretically impossible to recover a specific word from a stem, since one stem can be common to many words. One possibility, depending on your  I am not sure about support for Russian. I know tm supports Russian for its stopwords so maybe look into the stemCompletion language support as well. Also, are you sure you want to reverse stemming? You say in your question you want to find all possible roots; this isnt the reverse of stemming, this IS stemming. – Cybernetic Sep 10 '18 at 0:57

The question you are referencing contains an important piece of information which is often overlooked. What you require is known as "lemmatisation"- the reduction of inflected words to their canonical form. It is related but different from stemming and is still an open research question. It is particularly hard for languages with more complex morphology (English is not that hard). Wikipedia has a list of software you can try. Another tool I have used is TreeTagger- it is really fast and reasonably accurate, although it primary purpose is part-of-speech tagging and lemmatisation is just a bonus. Try googling for "statistical lemmatisation" (yes, I do have strong feelings about the statistical vs rule-based NLP)

Stemming, However, the two words differ in their flavor. Stemming usually refers to a crude heuristic process that chops off the ends of words in the hope of achieving this  In linguistic morphology and information retrieval, stemming is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form—generally a written word form. The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root.

You might look at the NCI Metathesaurus -- although mostly biomedical in nature, they offer examples of natural language processing and some open source toolsets for Java you might find useful by browsing their code.

Stemming and lemmatization, In natural language processing, there may come a time when you want your program to recognize that Understemming is the opposite issue. Stemming, in linguistic morphology and information retrieval science, is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form, generally a written word form. For grammatical reasons, documents are going to use different forms of a word, such as organize,

Stemming? Lemmatization? What?, Stemming is the process of producing morphological variants of a root/base word​. It is extension of Lovins stemmer in which suffixes are stored in the reversed  1) Tokenization: the process of segmenting text into words, clauses or sentences (here we will separate out words and remove punctuation). 2) Stemming: reducing related words to a common stem. 3) Removal of stop words: removal of commonly used words unlikely to be useful for learning.

Introduction to Stemming, Stemming algorithms, on the other hand, are processes that gather all words sharing the same stem with A reverse process is used to analyze Arabic words. Linguistic processing for stemming or lemmatization is often done by an additional plug-in component to the indexing process, and a number of such components exist, both commercial and open-source. The most common algorithm for stemming English, and one that has repeatedly been shown to be empirically very effective, is Porter's algorithm

Text, Speech and Dialogue: 5th International Conference, TSD 2002, , In the traditional sense of the concept of stemming, this algorithm is its reverse process. Rather than try and remove suffixes, the goal of a production algorithm is  Stemming is a kind of normalization for words. Normalization is a technique where a set of words in a sentence are converted into a sequence to shorten its lookup. The words which have the same meaning but have some variation according to the context or sentence are normalized. In another word, there is one root word, but there are many

Information Retrieval, A Practitioner's Guide to Natural Language Processing Dipanjan Sarkar The reverse process of obtaining the base form of a word is known as stemming. STEM Club: Reverse Engineering | Eva Varga says: February 6, 2014 at 8:51 am […] homeschool science blogger, Marci, when she shared a great printable she created for her kids, Reverse Engineering Printable Worksheets.