What is the difference between Stemming and Lemmatization in AI?

Whenever you are running some search, you are looking for relevant results not only for the given expression that you have typed in the respective search bar, but also for other potential forms of terms or words that you might have used. For instance, it is likely that you are looking for observing results containing the form “book” when you have typed “books” in the search bar.

The given procedure is made possible with the help of two distinct mechanisms –stemming and Lemmatization. The aim of the given processes turns out to be the same –minimizing the inflectional forms of terms or words into a common root or base. However, it is important to note that these two mechanisms are not the same. In this post, let us help you understand the major points of differences between stemming and Lemmatization in context with AI-based searching.

Differences Between Stemming and Lemmatization

The major points of differences lie in the manner in which these two processes work.

  • Stemming algorithms are known to work by slicing off the beginning or end of the word. The given mechanism is known to take into account a list of common prefixes & suffixes that could be easily found in some inflected term. The given form of indiscriminate slicing might turn out successful in some instances –but not at all times. This is the reason why experts report that the given approach might impose some limitations.

  • Lemmatization: This process, on the other hand, is known to take into regard the morphological analysis of terms or words. For achieving the same, it is essential to maintain detailed dictionaries that the given algorithm can glance through for linking the form back to the respective lemma.

Another important difference that needs highlighting is that the lemma serves to be the base form of all the respective inflectional forms. On the other hand, this is not the case with the stem. This is the reason why regular dictionaries are available as lists of lemmas, and not stems. This might turn out to have two major consequences:

  • Firstly, the stem could be same for inflectional forms of varying lemmas. This would translate into noise in the respective search results.

  • At the same time, the same lemma could correspond to various forms with varying stems. In this case, it is required to treat them in the form of the same term or word.

How Do the Mechanisms Work?

  • Stemming: There are different sets of algorithms that could be utilized in the stemming mechanism. In English, the most common algorithm is the Porter stemmer. The rules that are available in the given algorithm are categorized into multiple phases from one to five. The aim of the given roots is to minimize the words to its roots.

  • Lemmatization: The key aspect of the given mechanism is linguistics. For extracting proper lemma, it is important to look at the respective morphological analysis of every term. This would require including dictionaries for each language for providing the given type of analysis.