{"id":497060,"date":"2022-06-13T10:28:00","date_gmt":"2022-06-13T08:28:00","guid":{"rendered":"https:\/\/www.devoteam.com\/success-story\/ai-recommender-system-royal-belgian-football-association-vertex-ai\/"},"modified":"2022-06-13T10:28:00","modified_gmt":"2022-06-13T09:28:00","slug":"ai-recommender-system-royal-belgian-football-association-vertex-ai","status":"publish","type":"success-story","link":"https:\/\/devoteam.info\/en-pt\/success-story\/ai-recommender-system-royal-belgian-football-association-vertex-ai\/","title":{"rendered":"How Devoteam G Cloud built a next-level AI recommender system for the Royal Belgian Football Association using Vertex AI"},"content":{"rendered":"\n
\n
\n

The snapshot<\/h2>\n\n\n\n
\n
\n
\n

1<\/strong><\/p>\n\n\n\n

RBFA wanted to enhance user engagement and deliver personalised content.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

2<\/strong><\/p>\n\n\n\n

Devoteam developed a system for tailored content recommendations.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

3<\/strong><\/p>\n\n\n\n

Results? An automated, low-latency system for a personalised user experience.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n\n\n\n

\n
\"Quote\"<\/figure>\n\n\n\n

The recommender system from Devoteam G Cloud will enable us to deliver a greatly improved personalised experience to all of our users, and tackle more complex use-cases such as ads recommendations and content recommendations.<\/p>\n\n\n\n

\n\n\n\n
\n
\"\"<\/figure>\n\n\n\n
\n

Koen Landsheere
Agile digital IT manager @ Royal Belgian Football Association<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

About the customer<\/h2>\n\n\n\n

The Royal Belgian Football Association (RBFA) was founded on 1 September 1895. It is the official representative of Belgian football. They have many responsibilities going from managing the Belgian football teams like the Belgian Red Devils and Belgian Red Flames to assisting local teams with their organisation. In short, almost anyone interested in football in Belgium will at some point interact with the RBFA.<\/p>\n\n\n\n

As an important part of their business, the RBFA provides specialised football content to supporters through articles, videos, and quizzes. This ensures that football fans are always up-to-date with the latest news, in addition to putting interesting matches\/interviews\/initiatives in the spotlight.<\/p>\n\n\n\n

The Challenge<\/h2>\n\n\n\n

To keep users engaged, the RBFA wants to create a personalised experience for each of them. This concerns all the content that the RBFA produces, but also important advertisements from their partners, and products in their web shop. All these elements share one common denominator: they contain tags. Tags are minimalist word-length descriptions of what the entity (content, ad, or product) is about. For example, #red-devils, #futsal, or #disability-teams. <\/p>\n\n\n\n

Therefore, instead of directly recommending content, ads, or products, we can first recommend the most relevant tags for a user, and then join them to the related content, ads, and products.<\/p>\n\n\n\n

The Goal<\/h2>\n\n\n\n

The focus of the project is on recommending content to users. Being able to recommend personalised ads and products was left for the future, as it requires more complex integrations with RBFA\u2019s existing tools.<\/p>\n\n\n\n

To this end, we first developed tag recommendations using known interactions between users and tags through the smartphone application or website, that we then joined to content through tags.<\/p>\n\n\n\n

However, when developing recommender systems, one must tackle several challenges:<\/p>\n\n\n\n