Augmenting e-commerce product recommendations by analyzing customer personality

Marwade, Anwesh; Kumar, Nakul; Mundada, Shubham; Aghav, Jagannath

doi:10.1109/cicn.2017.8319380

Cited by 11 publications

(4 citation statements)

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“…As discussed earlier, the final output of a recommender system is to suggest products that may be of interest to the user [15]. These items can be shown to users using various web-based advertisements like google ads, by displaying in e-commerce websites or by sending promo messages.…”

Section: Visualization Of Recommendationsmentioning

confidence: 99%

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Pradeep¹,

M²,

Satyanarayana³

2020

INDJCSE

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The E-Commerce industry is a new way of shopping. Most manufacturers prefer to sell their products on E-commerce websites because of low maintenance and high returns. This paper highlights the application of data science and deep learning methodologies to drive the E-commerce business. The first part of the paper explains the role of data science to identify potential customers, items recommendations and fraud detections. Different stages of building E-commerce websites and the role of proper handling of data is then highlighted. The second part of the paper is about the use of deep learning approaches like Recurrent neural networks in analysing textual information is presented with a demonstration of three architectures. At last, the importance of convolutional neural networks in the E-commerce industry is presented. Fashion related images like dresses, shoes and bags are classified using two separate convolution neural network architectures.

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Section: Visualization Of Recommendationsmentioning

confidence: 99%

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Pradeep¹,

M²,

Satyanarayana³

2020

INDJCSE

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“…There have been many studies and research that discuss artificial intelligence in influencing product recommendations [14], the AI can influencing customer behavior in determining the items they want to buy [7]. and use in the world can improve marketing because it can increase sales and can connect from one business to another [2,15,16].…”

Section: Introductionmentioning

confidence: 99%

“…This study analyzes the personality types of customers in their daily e-commerce interactions [14] Use of artificial intelligence system to predict consumers' behaviors This paper using SEM and SPSS for analysis the data [24] Application Research of Computer Artificial Intelligence Technology in Electronic Commerce Information Retrieval System This paper will discuss about the data from searched word customer in the end [25] The…”

Section: Introductionmentioning

confidence: 99%

Digital Business Transformation: Analysis of the Effect Artificial Intelligence in E-Commerce’s Product Recommendation

Louis,

Noerlina,

Syahchari

2024

A.I.S.

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The purpose of this study is to determine whether artificial intelligence used in E-Commerce influences product recommendations for users. This study explains how much influence artificial intelligence on product recommendations supplied by E-commerce in terms of consumer behavior in making purchasing decisions. Research methods. This research used bibliometric analysis to find the mapping of this topic with articles period 2017 to 2023 from Scopus database. Of the 103 articles were showed by keyword and analyzing the articles according to the relate of the content about 29 articles were finally obtained. The research result is Artificial Intelligence has influence for E-commerce, recommendation system, decision support system, customer behaviour’s, and customer trust. Product recommendations have an impact on E-Commerce. Conclusion. However, from the literature review, founded that there are still a few journals discussing related to considerations to the implementation regarding the use of AI in e-commerce "Consumer behaviour", "Customer Trust", "Purchasing decisions". This study is also useful to generate additional AI-related research in e-commerce and unquestionably for a fresh subject will be covered especially in context of product recommendations on E-commerce.

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“…In the age of e-commerce, it is important for companies to develop web-based marketing strategies such as product bundling to increase revenue. The e-commerce industry predominantly uses various machine learning models for product recommendations and analyzing a customer's behavioral patterns, which play a crucial role in exposing customers to new products based on their online behaviour [2]. Psychology studies show that if customers are shown products suited to their personality type or complementing their lifestyle, the chances of buying them grows considerably [2].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning as a method of adapting offers to the clients

Bielecki

Ceglarski

Skublewska‐Paszkowska

2019

jcsi

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Recommendation systems are class of information filter applications whose main goal is to provide personalized recommendations. The main goal of the research was to compare two ways of creating personalized recommendations. The recommendation system was built on the basis of a content-based cognitive filtering method and on the basis of a collaborative filtering method based on user ratings. The conclusions of the research show the advantages and disadvantages of both methods.

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Augmenting e-commerce product recommendations by analyzing customer personality

Cited by 11 publications

References 1 publication

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Data Science and Deep Learning Applications in the E-Commerce Industry: A Survey

Digital Business Transformation: Analysis of the Effect Artificial Intelligence in E-Commerce’s Product Recommendation

Machine Learning as a method of adapting offers to the clients

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