In recent information explosion, contents in internet are multilingual and majority will be in
the form of natural languages. Processing of these natural languages for various language …

Many artificial intelligence studies focus on designing new neural network models or
optimizing hyperparameters to improve model accuracy. To develop a reliable model …

This study presents an efficient framework of deriving lemma from an inflected Bangla word
considering its parts-of-speech as context. Bangla is a morphologically rich Indo-Aryan …

The morphological variations of highly inflected languages that appear in a text impede the
progress of computer processing and root word determination tasks while extracting an …

Manual filtering becomes a tedious task for the recruiter as there are thousands of
candidates applying for a single job posting. In this paper, a Long Short-term Memory …

The process of strip** off affixes from a word to arrive at root word or lemma is known as
Lemmatization. The usefulness of lemmatizer in natural language operations cannot be …

Stemming is an important process in Information Retrieval (IR). Stem returned by stemmer
need not be always a valid dictionary word. While a lemma returned by lemmatizer is always …

Lemmatization is a natural language processing (NLP) based text normalization technique
that effectively improves data consistency and assists in context interpretation. Nevertheless …

Reducing a word to its original form called stemming is extremely important in the field of
natural language processing, especially to develop morphological analyzer and information …

Lemmatization is a Natural Language Processing (NLP) technique used to normalize text by
changing morphological derivations of words to their root forms. It is used as a core pre …