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Title: :  PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE
PaperId: :  23052
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23052
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
INDRAKUMAR R SBANNARI AMMAN INSTITUTE OF TECHNOLOGY
AKIL ADHARSH NBANNARI AMMAN INSTITUTE OF TECHNOLOGY
NISHA DEVI KBANNARI AMMAN INSTITUTE OF TECHNOLOGY

Abstract

COMPUTER ENGINEERING
Recommendation system, Similarity, personalization, content-based filtering, hybrid recommendation
In this era of rapid technological advancements, personalized recommendation systems powered by AI are gaining prominence. Such systems leverage machine learning algorithms to analyse user preferences, behaviour, and historical data to provide tailored recommendations in an E-Commerce website. By considering factors like user demographics, past purchases, reviews, and specifications (keywords), these systems aim to deliver accurate and relevant suggestions to individual users. The recommendation process typically involves several steps. Firstly, user data is collected, including demographic information, browsing history, and previous purchases. Collaborative filtering techniques compare a user's preferences with those of other similar users, recommending products that have been liked or purchased by users with comparable tastes. Additionally, explicit feedback such as ratings and reviews may be incorporated. Next, the system utilizes various AI techniques like collaborative filtering, content-based filtering, or hybrid approaches to process and analyse this data. To enhance the personalization aspect, AI models can be trained to adapt to individual user behaviour over time of period. Privacy and data security are critical considerations in personalized recommendation systems. User consent and anonymization techniques are employed to protect personal data and ensure compliance with data protection regulations. The ultimate goal of an AI-based personalized recommendation system for E-Commerce is to simplify the decision-making process for users and provide them with a curated list of options that best match their preference sand needs. By leveraging ML algorithms, these systems strive to enhance user satisfaction, increase customer engagement, and improve the overall shopping experience in the E-commerce website.

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IJARIIE INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. "PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 2257-2265
MLA INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. "PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 2257-2265.
APA INDRAKUMAR R S, AKIL ADHARSH N, & NISHA DEVI K. (2024). PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 2257-2265.
Chicago INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. "PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 2257-2265.
Oxford INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. 'PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 2257-2265. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/PERSONALISED_RECOMMENDATION_SYSTEM_FOR__E_COMMERCE_ijariie23052.pdf (Accessed : 04 April 2024).
Harvard INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. (2024) 'PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 2257-2265IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/PERSONALISED_RECOMMENDATION_SYSTEM_FOR__E_COMMERCE_ijariie23052.pdf (Accessed : 04 April 2024)
IEEE INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K, "PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 2257-2265, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/PERSONALISED_RECOMMENDATION_SYSTEM_FOR__E_COMMERCE_ijariie23052.pdf [Accessed : 04 April 2024].
Turabian INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. "PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 (04 April 2024).
Vancouver INDRAKUMAR R S, AKIL ADHARSH N, and NISHA DEVI K. PERSONALISED RECOMMENDATION SYSTEM FOR E-COMMERCE. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : 04 April 2024]; 10(2) : 2257-2265. Available from: https://ijariie.com/AdminUploadPdf/PERSONALISED_RECOMMENDATION_SYSTEM_FOR__E_COMMERCE_ijariie23052.pdf
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