Discussion 4 Basket Analysis

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Collaborative Filting

This gif illustrates the most commonly used recomendation system model: Collaborative Filting.Collaborative filtering can answer a question “What items do users with interests similar to yours like? The draw back of collaborative filtering is that it is most effective when there is a rich history of user preferences or behavior, and would not be as useful if such history do not exist, such as in the early phase of new products.

Market Basket Recommendation

Market basket recommendation

Figure

Market basket analysis is mostly used in the retail business, is where you take inventory and point-of-sale data to predict which combinations of products will sell the best. Market basket analysis and product recommendation has been a common practice implemented by businesses in the retail industry for years. It is an association based recommendation system, and has recently gain its momentum to other industries. Above figure illustrates the typical scenario of where market basket analysis is from.

ents/3_rules.png) https://stats.stackexchange.com/questions/256012/item-item-collaborative-filtering-vs-market-basket-analysis https://www.knime.com/knime-applications/market-basket-analysis-and-recommendation-engines https://nealanalytics.com/understanding-market-basket-analysis-product-recommendation/