The rapid growth of electronic documents are causing problems like unstructured data that
need more time and effort to search a relevant document. Text Document Classification …

Text stemming is one of the basic preprocessing step for Natural Language Processing
applications which is used to transform different word forms into a standard root form. For …

The exponential increase in textual unstructured digital data creates significant demand for
advanced and smart stemming systems. As a preprocessing stage, stemming is applied in …

Stemming is the basic operation in Natural language processing (NLP) to remove
derivational and inflectional affixes without performing a morphological analysis. This …

In the field of natural language processing, machine translation is a colossally developing
research area that helps humans communicate more effectively by bridging the linguistic …

The current gap which appears in the Quran ontology population domain is stemming
impact analysis on Indonesian Quran translation and their Tafsir to develop ontology …

Named Entity Recognition (NER) is a natural language processing task that has been widely
explored for different languages in the recent decade but is still an under-researched area …

With the advent of globalization epoch, the Internet-based resources for Urdu are increasing
in depth and breadth at a higher pace than ever and thus require a mechanism for …

Lemmatization aims at returning the root form of a word. The lemmatizer is envisioned as a
vital instrument that can assist in many Natural Language Processing (NLP) tasks. These …

Stemming is a common word conflation method that perceives stems embedded in the
words and decreases them to their stem (root) by conflating all the morphologically related …