NCA-GENL Question 118
Select 3You are working with a large dataset consisting of customer purchase history for an e-commerce platform. Your goal is to identify patterns in customer behavior to improve product recommendations. Which of the following steps would be most appropriate for extracting meaningful insights from the dataset using data mining and visualization techniques?
- A
Perform clustering to group customers based on similar purchasing behaviors.
- B
Use a pre-trained large language model to summarize the dataset.
- C
Generate a correlation matrix to identify relationships between product categories.
- D
Visualize customer purchase trends over time using line charts and heatmaps.
- E
Apply reinforcement learning to predict future customer purchases.
Show answer and explanation
Correct answers: A, C, D
Explanation
Extracting insights from large datasets involves using data mining techniques like clustering to identify patterns, generating correlation matrices to uncover relationships, and employing data visualization to interpret trends and distributions. These methods provide a solid foundation for understanding customer behavior, which can then be used to improve product recommendations.
- A. Correct.
Clustering is a common data mining technique used to group similar entities, such as customers with similar purchasing behaviors, to uncover patterns.
- B. Incorrect.
While large language models are powerful, they are not typically used for summarizing or analyzing structured datasets like customer purchase history.
- C. Correct.
A correlation matrix helps identify relationships between variables, such as product categories, and is a key step in gaining insights from data.
- D. Correct.
Visualizing trends over time using charts and heatmaps can reveal seasonality, spikes in purchases, or other temporal patterns in customer behavior.
- E. Incorrect.
Reinforcement learning is a machine learning technique used for decision-making in dynamic environments, but it is not directly related to data mining or visualization for extracting insights.