A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems - Guevara Fernandez, Alexander (2023)
Recommendation systems are information filtering tools that help present elements to users based on their tastes and preferences, for example, making suggestions for household items or specific products for a user. Currently, there are various types of recommendation systems. recommendation (SR) to address the increase in information on the Internet by companies and thus improve efficiency in their product sales processes through recommendations. Likewise, there are different types of recommendation systems that use specific techniques that meet the business objectives such as popularity systems that focus on the popularity of a product based on the criteria of likes, comments, the time a customer took to review the product, content that based on history of a client tries to predict what the user is looking for and suggest products in relation to the client’s possible tastes and collaborative filtering in recommendation systems generate recommendations by analyzing data, identifying users and comparing the information of the user’s profile and that of a group of users, in Based on the aforementioned, this research article proposes a review of methods, techniques and algorithms for electrical product recommendation systems, with the objective of supporting and facilitating decision making as well as helping in the continuous improvement of companies and in this way increase the efficiency of the systems at the time of their implementation.