AIMC Topic: Commerce

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Alcohol outlets and firearm violence: a place-based case-control study using satellite imagery and machine learning.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention Aug 29, 2019
INTRODUCTION: This article proposes a novel method for matching places based on visual similarity, using high-resolution satellite imagery and machine learning. This approach strengthens comparisons when the built environment is a potential confounde...
Residence Characteristics Alcoholic Beverages Commerce Case-Control Studies Urban Population Violence Satellite Imagery Wounds, Gunshot Philadelphia Firearms Humans Machine Learning
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Can we predict firms' innovativeness? The identification of innovation performers in an Italian region through a supervised learning approach.

PloS one Jun 11, 2019
The study shows the feasibility of predicting firms' expenditures in innovation, as reported in the Community Innovation Survey, applying a supervised machine-learning approach on a sample of Italian firms. Using an integrated dataset of administrati...
Italy Supervised Machine Learning Commerce Humans Models, Theoretical
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Do street-level scene perceptions affect housing prices in Chinese megacities? An analysis using open access datasets and deep learning.

PloS one May 30, 2019
Many studies have explored the relationship between housing prices and environmental characteristics using the hedonic price model (HPM). However, few studies have deeply examined the impact of scene perception near residential units on housing price...
Humans Deep Learning Housing Commerce City Planning Beijing China Cities
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Predicting nationwide obesity from food sales using machine learning.

Health informatics journal May 19, 2019
The obesity epidemic progresses everywhere across the globe, and implementing frequent nationwide surveys to measure the percentage of obese population is costly. Conversely, country-level food sales information can be accessed inexpensively through ...
Obesity Food Commerce Machine Learning Support Vector Machine Humans
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A New Approach for Construction of Geodemographic Segmentation Model and Prediction Analysis.

Computational intelligence and neuroscience May 13, 2019
Customer retention is invariably the top priority of all consumer businesses, and certainly it is one of the most critical challenges as well. Identifying and gaining insights into the most probable cause of churn can save from five to ten times in t...
Humans Machine Learning Forecasting Consumer Behavior Commerce
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Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data.

PloS one Feb 15, 2019
Forecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. We propose a model, called the feature fusion long short-term memory-convolutional neural network (LST...
Commerce Models, Economic Neural Networks, Computer
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Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.

Science and engineering ethics Feb 14, 2019
Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI t...
Social Media Liability, Legal Artificial Intelligence Forecasting Fraud Sex Offenses Interdisciplinary Research Commerce Crime Humans Drug Trafficking
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Stock Market Forecasting Using Restricted Gene Expression Programming.

Computational intelligence and neuroscience Feb 5, 2019
Stock index prediction is considered as a difficult task in the past decade. In order to predict stock index accurately, this paper proposes a novel prediction method based on S-system model. Restricted gene expression programming (RGEP) is proposed ...
Marketing Models, Economic Commerce Forecasting Models, Genetic Neural Networks, Computer Algorithms Humans
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Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators.

Neural computation Aug 27, 2018
This study focuses on predicting stock closing prices by using recurrent neural networks (RNNs). A long short-term memory (LSTM) model, a type of RNN coupled with stock basic trading data and technical indicators, is introduced as a novel method to p...
Neural Networks, Computer Models, Economic Commerce
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Using machine learning to evaluate treatment effects in multiple-group interrupted time series analysis.

Journal of evaluation in clinical practice Jun 11, 2018
RATIONALE, AIMS, AND OBJECTIVES: Interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single treatment unit's outcome is studied over time, and the intervention is expected to "interrupt" the level and/or trend of th...
Smoking Prevention Commerce Interrupted Time Series Analysis Research Design Propensity Score Evaluation Studies as Topic California Humans Treatment Outcome Program Evaluation Discriminant Analysis Machine Learning
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