Stemming is one of the basic steps in natural language processing applications such as
information retrieval, parts of speech tagging, syntactic parsing and machine translation, etc …

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

Urdu language is used by approximately 200 million people for spoken and written
communications. The bulk of unstructured Urdu textual data is available in the world. We can …

The rapid increase in the quantity of Kurdish documents over the last several years has
created a need for improving information accuracy and precision in text classification and …

Stemming is a procedure that conflates morphologically related terms into a single term
without doing complete morphological analysis. Urdu language raises several challenges to …

Increasing size of web leads to relevant information extraction by traditional and last query
expansion methods not to be efficient and encounter an essential challenge. Therefore, to …

Word stemming is one of the most significant factors that affect the performance of a Natural
Language Processing (NLP) application such as Information Retrieval (IR) system, part of …

One of the important issues in natural language processing and information retrieval is the
automatic extraction of the word's stem. Both statistical and rule-based approaches for …

Persian is a challenging language in the field of NLP. Right-to-left orthography, complex
morphology, complicated grammatical rules, and different forms of letters make it an …

Urdu language raises several challenges to Natural Language Processing (NLP) largely
due to its rich morphology. In this language, morphological processing becomes particularly …