användarobjektmatriser

Användarobjektmatriser, often translated as user-item matrices, are a fundamental concept in recommender systems and collaborative filtering. They are a data structure used to represent the interactions between users and items. In its simplest form, a user-item matrix is a two-dimensional array where rows represent users and columns represent items. The cells within the matrix contain a value indicating the relationship between a specific user and a specific item.

This value can take various forms depending on the type of interaction being modeled. It could be a binary value (0 or 1) indicating whether a user has interacted with an item (e.g., purchased, viewed, rated) or not. Alternatively, it could be a numerical rating provided by the user for an item, such as a score on a scale of 1 to 5. In some cases, the value might represent the intensity or duration of an interaction, like the time spent watching a video.

The primary purpose of a user-item matrix is to facilitate the discovery of patterns and relationships. By analyzing this matrix, recommender systems can identify which items are similar to each other based on user preferences, or which users have similar tastes. This information is then used to predict what items a user might like or be interested in, even if they haven't interacted with them before. Sparsity is a common characteristic of user-item matrices, meaning most cells are empty because a given user has only interacted with a small fraction of the available items. Various techniques are employed to handle this sparsity and extract meaningful insights.