The LikeMinds Recommendation Engines

LikeMinds Recommendation Engines communicate with a relational database and generate recommendations. Learn about the three types of recommendation engines, Preference engine, Clickstream engine, and Item Affinity engine.

Following is a description of the three types of recommendation engines:

• Preference engine: This engine generates recommendations using patented collaborative filtering algorithms based on users' item ratings.

• Clickstream engine: This engine, which also accesses transaction information, generates recommendations based on users' actions as they navigate a Web site; that is, the history of user "clicks" during website visits, and the items that users view, click, and add to their shopping carts.

• Item Affinity engine: This engine generates recommendations based on the history of the user's site browsing activity. It matches a currently selected product with a second product that the user would most likely want to purchase along with the first product. For example, if a user is purchasing groceries and adds French onion soup to the shopping cart, the Item Affinity engine could recommend Gruyere cheese to go with it.

• Preference Engine
  The Preference Engine uses explicitly stated user preferences to make highly accurate recommendations for products and content that the website visitors like.

• Clickstream Engine
  Based on navigational data gathered as customers browse the Web site, the Clickstream Engine tracks clickstream (or rating) behavior and generates recommendations based on mentors who exhibit similar content/product affinities.

• Item Affinity Engine
  The Item Affinity Engine generates recommendations based on any transactional history available, such as shopping cart activity, external legacy transactions, and web transaction completely unrelated to shopping cart activity (page views, product inquiries, searches, and so on).

Parent: LikeMinds Recommendations