How to cite (IEEE): E. Anaam, S. Haw, & P. Naveen "Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM," JOIV : International Journal on Informatics Visualization, vol. 6, no. 2-2, , pp. 553-560, Aug. 2022. https://doi.org/10.30630/joiv.6.2-2.1043

How to cite (APA): Anaam, E., Haw, S., & Naveen, P. (2022). Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM. JOIV : International Journal on Informatics Visualization, 6(2-2), 553-560. https://doi.org/10.30630/joiv.6.2-2.1043

How to cite (Chicago): Anaam, Elham Abdulwahab, Haw, Su-Cheng, AND Naveen, Palanichamy. "Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM" JOIV : International Journal on Informatics Visualization [Online], Volume 6 Number 2-2 (7 August 2022) https://doi.org/10.30630/joiv.6.2-2.1043

How to cite (Vancouver): Anaam E, Haw S, & Naveen P . Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM. JOIV : International Journal on Informatics Visualization [Online]. 2022 Aug; 6(2-2):553-560. https://doi.org/10.30630/joiv.6.2-2.1043

How to cite (Harvard): Anaam, E., Haw, S., & Naveen, P. ,2022. Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM. JOIV : International Journal on Informatics Visualization, [Online] 6(2-2), pp. 553-560. https://doi.org/10.30630/joiv.6.2-2.1043

How to cite (MLA8): Anaam, Elham Abdulwahab, Su-Cheng Haw, & Palanichamy Naveen. "Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM." JOIV : International Journal on Informatics Visualization [Online], 6.2-2 (2022): 553-560. Web. 2 Oct. 2022 , https://doi.org/10.30630/joiv.6.2-2.1043

BibTex Citation Data :

@article{JOIV1043,
    	author = {Elham Abdulwahab Anaam and Su-Cheng Haw and Palanichamy Naveen},
    	title = {Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM},
    	journal = {JOIV : International Journal on Informatics Visualization},
    	volume = {6},
    	number = {2-2},
    	year = {2022},
    	keywords = {Hybrid recommendation technique; recommender system; E-CRM; Fuzzy-AHP; hybrid fuzzy.},
    	abstract = {To create a personalized E-CRM recommendation system, the electronic customer relationship management system needs to investigate low accuracy and lack of personalization through applied hybrid recommendation system techniques such as fuzzy and AHP. The main purpose of this research is to enhance the accuracy and deep understanding of common recommendation techniques in E-CRM. The fuzzy and AHP techniques have been used in the current study to the available information of objects and to extend recommendation areas. The findings indicate that each of these strategies is appropriate for a recommendation system in a technological environment. The present study makes several noteworthy contributions to the fuzzy Analytic Hierarchy Process (AHP) and has the maximum accuracy of any of these approaches, with 66.67% of accuracy. However, AHP outperforms all others in terms of time complexity. We advocate the concept and implementation of an intelligent business recommendation system dependent on a hybrid approval algorithm that serves as a model for E–CRM recommendation systems. This recommendation system's whole design revolves on the hybrid recommendation system. The systems additionally incorporate the recommendation modules and the recommendation measurement updating framework. The recommendation modules include the formulation and development of material recommendation algorithms, element collaborative filtering recommendation algorithms, and demography-based recommendation algorithms.},
        	issn = {2549-9904},    	pages = {553--560},    	doi = {10.30630/joiv.6.2-2.1043},
        	url = {https://joiv.org/index.php/joiv/article/view/1043}
    }
    

Refworks Citation Data :

@article{{JOIV}{1043}, author = {Anaam, E., Haw, S., Naveen, P.}, title = {Applied Fuzzy and Analytic Hierarchy Process in Hybrid Recommendation Approaches for E-CRM}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {6}, number = {2-2}, year = {2022}, doi = {10.30630/joiv.6.2-2.1043}, url = {} }