AIMC Topic: Consumer Behavior

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The design of consumer behavior prediction and optimization model by integrating DQN and LSTM.

PloS one
Amidst the rapid evolution of e-commerce and the growing abundance of consumer shopping data, accurately identifying consumer interests and enabling targeted outreach has become a critical focus for merchants and researchers. This study introduces th...

The analysis of dynamic evaluation of online shopping satisfaction based on the recurrent neural network model.

Scientific reports
This work aims to accurately understand user satisfaction in online shopping, reflecting user preferences and promoting the development of online shopping. This work explores a behavioral prediction method for online shopping users using a Recurrent ...

Enhanced E-commerce decision-making through sentiment analysis using machine learning-based approaches and IoT.

PloS one
E-commerce is a vital component of the world economy, providing people with a simple and convenient method for shopping and enabling businesses to expand into new global markets. Improving e-commerce decision-making by utilizing IoT and machine intel...

Application of machine learning in predicting consumer behavior and precision marketing.

PloS one
with the intensification of market competition and the complexity of consumer behavior, enterprises are faced with the challenge of how to accurately identify potential customers and improve user conversion rate. This paper aims to study the applicat...

The analysis of marketing performance in E-commerce live broadcast platform based on big data and deep learning.

Scientific reports
This study aims to conduct a comprehensive and in-depth analysis of the marketing performance of e-commerce live broadcast platforms based on big data management technology and deep learning. Firstly, by synthesizing large-scale datasets and surveys,...

Session interest model for CTR prediction based on feature co-action network.

Scientific reports
The main purpose of click-prediction models is to predict the probability of customers clicking on products and provide support for advertising decisions of businesses. However, most previous models often use deep neural networks to capture implicit ...

Consumer views of functional electrical stimulation and robotic exoskeleton in SCI rehabilitation: A mini review.

Artificial organs
BACKGROUND: Functional electrical stimulation (FES) and robotic exoskeletons represent emerging technologies with significant potential for restoring critical physical functions such as standing and walking-functions that are most susceptible after s...

Profiling the AI speaker user: Machine learning insights into consumer adoption patterns.

PloS one
The objective of this study is to identify the characteristics of users of AI speakers and predict potential consumers, with the aim of supporting effective advertising and marketing strategies in the fast-evolving media technology landscape. To do s...

Robots in the kitchen: The automation of food preparation in restaurants and the compounding effects of perceived love and disgust on consumer evaluations.

Appetite
Restaurants are swiftly embracing automation to prepare food, experimenting with innovations from robotic arms for frying foods to pizza-making robots. While these advances promise to enhance efficiency and productivity, their impact on consumer psyc...

Prediction of future customer needs using machine learning across multiple product categories.

PloS one
In recent years, computational approaches for extracting customer needs from user generated content have been proposed. However, there is a lack of studies that focus on extracting unmet needs for future popular products. Therefore, this study presen...