Stemming is the main step used for handling the morphologically rich languages such as Arabic. It is usually used in several fields such as Natural Language Processing, Information Retrieval (IR), and Text Mining. The goal of stemming is to reduce inflected or derived words to their base form. Since the Arabic language is an inflectional language and mainly depends on roots and patterns to generate words, this stemmer was developed based on the interaction between roots and patterns. The approach adopted for its development is similar to that used to develop the lemmatizer. The achieved accuracies are 96.93% and 96.56% for respectively the Quranic corpus “Al-Mus’haf” and the NEMLAR corpus.

For further details, please check the following paper :

  • M. Boudchiche and A. Mazroui, . “Spline functions for Arabic morphological disambiguation, Applied Computing and Informatics, https://doi.org/10.1016/j.aci.2020.02.002.
  • Zeroual, I., Boudchiche, M., Mazroui, A., Lakhouaja, A., . “Developing and performance evaluation of a new Arabic heavy/light stemmer”, In: Proceedings of the second International Conference on Big Data, Cloud and Applications, Tetuan, (Morocco), March 29-30, 2017. ISBN: 978-1-4503-4852-2. DOI: 10.1145/3090354.3090371

Source

You have the opportunity to download the source code for stemming from Alkhalil official website.

Download Source

Jar

You have the opportunity to download the jar file for stemming from Alkhalil official website.

Download Jar

Rest API

You have the opportunity to download the Rest API for the Stemmer.

Download API

ALKHALIL Demofor stemming Module




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RESTful Web API Code Snippets for stemming Module

API code examples in popular programming languages such as Java, Python, and JavaScript. These code snippets allow you to effectively utilize the API and integrate it into your projects for the stemming module.

							
import requests

# Get result in text format
url = "http://oujda-nlp-team.net:8080/api/Stemmer"
text_input = "##############################"

data = {"textinput": text_input}
response = requests.post(url, data=data)

if response.status_code == 200:
    result = response.text
    print(f"Result in text format: {result}")
else:
    print("Error during API request.")

# Get result in JSON format
# text = "##############################"
# url = "http://oujda-nlp-team.net:8080/api/Apistm/" + text
# response = requests.get(url)
# if response.status_code == 200:
#     result = response.text
#     print(f"Result in JSON format: {result}")
# else:
#     print("Error during API request.")							
								
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