Development of AI/ML-Based Recommendation Systems and Solutions
A recommendation system is a software program that predicts which product or services will be of interest to a user based on certain information about their profile.
What is the ML-Based Recommendation System for?
The purpose of a recommendation system is to inform a user about products or services they might be most interested in at a given moment.
The customer receives information, and the platform makes a profit by providing quality services.
Services are not necessarily direct selling of the product on offer.
The platform can also earn a commission or just increase its users’ loyalty, which then turns into advertising and other types of revenue.
How We Can Help / Methods of Recommendation System Development
If the customer has bought a vacuum cleaner, now they need bags, filters, extra brushes, and perhaps some other attachments, for example, a crevice tool for vacuuming corners.
Recommendations based on characteristics of items
If the customer likes action movies starring Daniel Craig, they might also like the Bourne franchise.
- Item-based recommendations: searching for items similar to those that the customer already likes. For example, if someone likes iceberg lettuce, they might also like frisée.
- User-based recommendations: searching for users that are similar to each other and recommending to one of them the items that others like. For example, a customer buys salsa sauce – the system finds other customers that share some set of characteristics with the said customer and also buy salsa sauce. And if these customers buy not only salsa sauce but also pasta and sandwiches, then the said customer might also need pasta and sandwiches.
Learning based on support vector machines, linear discriminant analysis, singular value decomposition for implicit functions.
Social & interest graphs
This method is based on trust and human social interactions. The user that has friends who are Metallica fans, might also like it. If the user reads articles about artificial intelligence, they might also be interested in startups developing new AI-based solutions.
Hybrid combinations of any methods listed above.
How We Can Help / Solution / Action Plan
- Business processes analysis and suggestion of optimal and most effective AI/ML usage scenarios.
- Defining the problem in the language of business processes and in the language understood by data scientists.
- Preparing the statement of work.
- MVP development.
- Testing and development of the final version of the product.
- Software support and updating.