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ISSN Number : XXXXXXXXX
Journal DOI number : XXXXXXXXX
Paper Title : A Study on Customer Review Based Product Recommendation in E-Commerce Using Artificial Intelligence
Authors : Dr. Syed Haseeb Osman
DOI Link : Na
Abstract :
Recommendation plays a very vital role in human life. Human beings rely a lot on recommendations from their daily routines to taking any big decision i.e., purchasing new things, organizing a function, recruiting a resource, buying furniture, or a new home. People reliance on recommendations and take their decisions based on the recommendation received from various sources. As the title suggests our recommendation system is based on customers’ reviews. While shopping through an e-commerce website, if the customer gets confused in selecting a product out of many available options, then the e-commerce platform provides a comparison option based on the features of the product, but what if the user can read the reviews of the product and then can decide that with which product, he/she should go for purchase. Further, it is very much difficult or we can say next to impossible for the customers to walk through the thousands of available reviews of any single product and then compare with other product to decide that with which product he/she should proceed for purchase. To recommend a product based on reviews we need to deal with the text and hence improved frequent pattern mining has been implemented to extract the relevant content and finally artificial intelligence applied to the extracted relevant content. We have also tested our output in a machine learning algorithm named Random Tree to validate our developed algorithm. Our proposed framework is divided into four phases, which include phase 1 - Products on the e-commerce website. Phase 2 - Users’ reviews and ratings. Phase 3 - Improved frequent pattern mining. And in final Phase 4 - Artificial Intelligence has been implemented.
Keywords : E-commerce, Artificial Intelligence,Review, Rating, Recommendation System, Frequent Pattern Mining,
Available at : https://discoveryjournal.in/dashboard1/papers/DISCOVERY2602235472.pdf
Publication Details :
Registration ID DISCOVERY32
Published Paper ID DISCOVERY2602235472
Published in Volume 1, Issue 1, March 2023
Page number 39-46
ISSN Number XXXXXXX
Journal DOI number : XXXXXXXXX
Paper Title : A Study on Customer Review Based Product Recommendation in E-Commerce Using Artificial Intelligence
Authors : Dr. Syed Haseeb Osman
DOI Link : Na
Abstract :
Recommendation plays a very vital role in human life. Human beings rely a lot on recommendations from their daily routines to taking any big decision i.e., purchasing new things, organizing a function, recruiting a resource, buying furniture, or a new home. People reliance on recommendations and take their decisions based on the recommendation received from various sources. As the title suggests our recommendation system is based on customers’ reviews. While shopping through an e-commerce website, if the customer gets confused in selecting a product out of many available options, then the e-commerce platform provides a comparison option based on the features of the product, but what if the user can read the reviews of the product and then can decide that with which product, he/she should go for purchase. Further, it is very much difficult or we can say next to impossible for the customers to walk through the thousands of available reviews of any single product and then compare with other product to decide that with which product he/she should proceed for purchase. To recommend a product based on reviews we need to deal with the text and hence improved frequent pattern mining has been implemented to extract the relevant content and finally artificial intelligence applied to the extracted relevant content. We have also tested our output in a machine learning algorithm named Random Tree to validate our developed algorithm. Our proposed framework is divided into four phases, which include phase 1 - Products on the e-commerce website. Phase 2 - Users’ reviews and ratings. Phase 3 - Improved frequent pattern mining. And in final Phase 4 - Artificial Intelligence has been implemented.
Keywords : E-commerce, Artificial Intelligence,Review, Rating, Recommendation System, Frequent Pattern Mining,
Available at : https://discoveryjournal.in/dashboard1/papers/DISCOVERY2602235472.pdf
Publication Details :
Registration ID DISCOVERY32
Published Paper ID DISCOVERY2602235472
Published in Volume 1, Issue 1, March 2023
Page number 39-46
ISSN Number XXXXXXX
Call For Papers
Frequency: 12 Issue per year
Paper Submission: Throughout the Month
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Areas Covered: Multidisciplinary
Accepted Language: Multiple Languages
Journal Type: Online (e-Journal)
Paper Submission: Throughout the Month
Acceptance Notification: Within 2 days
Areas Covered: Multidisciplinary
Accepted Language: Multiple Languages
Journal Type: Online (e-Journal)
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