Call for Papers:Vol.11 Issue.3

Submission
Last date		 28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms
PaperId: :  23847
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 3 2024
DUI:    16.0415/IJARIIE-23847
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Shobha GVidya Vikas Institute of Engineering & Institute of Engineering & Technology
Akhila K SVidya Vikas Institute of Engineering & Institute of Engineering & Technology
Chandana KVidya Vikas Institute of Engineering & Institute of Engineering & Technology
Hruthik T MVidya Vikas Institute of Engineering & Institute of Engineering & Technology
Avighna S GowdaVidya Vikas Institute of Engineering & Institute of Engineering & Technology

Abstract

Machine Learning
Apriori, Eclat, Frequent Itemset, Association Rule
Client segmentation and request strategy optimization are pivotal for retail operations, whether in physical promenades or e-commerce platforms. using association rules learning algorithms like Apriori and ECLAT plays a vital part in understanding client geste and preferences to achieve these pretensions. Apriori is famed for relating frequent item sets in a dataset and establishing association rules grounded on these item sets. For case, if guests frequently buy particulars A and B together, Apriori will induce a rule reflecting this association. ECLAT (Equivalence Class Transformation) algorithm, on the other hand, exploits the perpendicular data format and utilizes a depth-first hunt strategy to efficiently booby-trap frequent item sets. These algorithms enable businesses to member guests grounded on their interests and purchase geste. This segmentation facilitates targeted marketing strategies, allowing elevations and announcements to be acclimatized to specific client groups. These algorithms also help in relating arising request trends, allowing businesses to acclimate strategies consequently. By assaying literal data, businesses can describe shifts in consumer preferences and subsidize them with targeted juggernauts or new product lines. This visionary approach ensures competitiveness and fosters long-term client connections, driving growth and profitability. For illustration, if a member of guests constantly purchases electronics and accessories, the business can run targeted juggernauts or offer substantiated recommendations in these orders. perceptivity deduced from association rule literacy also informs the development of recommender systems, enhancing the shopping experience for guests. These systems give substantiated product recommendations grounded on one purchase or browsing history, thereby adding client satisfaction and fostering fidelity. In summary, Apriori and ECLAT algorithms offer precious tools for client segmentation and request strategy optimization in retail. By understanding client geste and preferences through these algorithms, businesses can conform their immolations and marketing strategies effectively to meet client requirements websites provide numerous client-grounded features such as recommending products grounded on client browsing history, recommending analogous products, constantly bought together products, standing for the bought products. But all these recommendations are universal, published to all orders of guests.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. "A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 3 2024 Page 1503-1508
MLA Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. "A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms." International Journal Of Advance Research And Innovative Ideas In Education 10.3(2024) : 1503-1508.
APA Shobha G, Akhila K S, Chandana K, Hruthik T M, & Avighna S Gowda. (2024). A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms. International Journal Of Advance Research And Innovative Ideas In Education, 10(3), 1503-1508.
Chicago Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. "A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 3 (2024) : 1503-1508.
Oxford Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. 'A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, 2024, p. 1503-1508. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_Real_Time_E_Commerce_Application_for_Customer_Segmentation_and_Advertisements_Recommendation_Using_ML_Algorithms_ijariie23847.pdf (Accessed : ).
Harvard Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. (2024) 'A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms', International Journal Of Advance Research And Innovative Ideas In Education, 10(3), pp. 1503-1508IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_Real_Time_E_Commerce_Application_for_Customer_Segmentation_and_Advertisements_Recommendation_Using_ML_Algorithms_ijariie23847.pdf (Accessed : )
IEEE Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda, "A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, pp. 1503-1508, May-Jun 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_Real_Time_E_Commerce_Application_for_Customer_Segmentation_and_Advertisements_Recommendation_Using_ML_Algorithms_ijariie23847.pdf [Accessed : ].
Turabian Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. "A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 3 ().
Vancouver Shobha G, Akhila K S, Chandana K, Hruthik T M, and Avighna S Gowda. A Real Time E-Commerce Application for Customer Segmentation and Advertisements Recommendation Using ML Algorithms. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(3) : 1503-1508. Available from: https://ijariie.com/AdminUploadPdf/A_Real_Time_E_Commerce_Application_for_Customer_Segmentation_and_Advertisements_Recommendation_Using_ML_Algorithms_ijariie23847.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
AI-Powered Resume Generation: A Streamlit-Based System Using PyTorch for Intelligent Career ProfilingComputer EngineeringAditi Meshram Download
AI based object color detection and sorting automationRobotics and AutomationBHUVAN THEJASWI T Download
Advanced knowledge on Synthetic Data Generation Using GANs for Medical Imaging ApplicationsArtificial IntelligenceRajeev Ranjan Download
Information on Cognitive AI Assistants for Visually Impaired Navigation SupportComputer ScienceNagaraj.H Download
Speech Emotion AI for Mental Health Monitoring in Call CentersComputer ScienceGowtham Kumar Download
Multi-Agent Reinforcement Learning for Coordinated Drone SwarmsComputer ScienceDeepak Gowda Download
AI-Based Soil Health Monitoring Using Remote Sensing and Deep LearningArtificial IntelligenceChethan Nagraj Download
Dynamic Criminal Network Link Forecasting via Deep Reinforcement LearningDeep LearningSrikant Tayade Download
Virtual Try-On-Enhancing Fashion Exploration for Gen-ZDeep Learning & Generative ModelsAnushka Mane Download
To Develop an EMG-Based Expert System for the Detection of Wrist Flexion and ExtensionArtificial Intelligence and Data ScienceRohit Mehta Download
LUNG CANCER PREDICTION AND DETECTION USING MLCOMPUTER SCIENCE & ENGINEERINGRASHMI T N Download
NewsTrust: AI-Driven News Verification with Social Publishing FeaturesArtificial IntelligenceRaj Mehta Download
Deepfake Technology: A Cybersecurity Threat and Counter Measures.Computer Engineering (Data Science)Chinmay Jitendra Dhamangaonkar Download
Predicting the stock market using machine learning algorithms: evidence from India and BrazilArtificial Intelligence and Machine LearningPrince Das Adhikary Download
Smart Diagnostic Systems for Infectious DiseasesArtificial Intelligence (AI)Kumar. S Download
12