CGV opens’Big Data Movie Recommendation’ exhibition

[Daily Economy Star Today Reporter Yang So-young]

What movie would the audience want to see again on the screen this summer?

CGV hosts ‘Big Data Movie Recommendation’ planning exhibition from 9th to 15th. For this exhibition, CGV carefully selected re-release recommendations by genre based on a variety of big data materials and machine learning techniques, such as movie content information and characteristics of CGV audiences, as well as audience numbers and satisfaction at the time of release.

As for the screenings, the musical movie ‘Mamma Mia! 2’, the horror movie ‘Get Out’, and the action movie ‘Monday is gone’ were selected. This is an opportunity to watch movies that gained popularity at the time of release for 6,000 won.

‘Mamma Mia! 2’ is a special and touching musical film where Sophie (Amanda Cyprid) learns a solo as a result of the brilliant memories of her mother Donna (Maryl Strip). As a sequel to ‘Mamma Mia!’ (2008), it gained popularity by attracting more than 229 million audiences when it was released in 2018.

‘Get Out’ is a movie about a black male Chris (Daniel Kaluya) having a weekend visit to his lover, a white girlfriend, Rose (Allison Williams)’s parents’ home. This is a new form of horror film made by mixing comedy and horror based on racial discrimination based on comedian Jordan Phil’s debut film.

Lastly, it is a work that caught the eye of the story of the seven twins sharing a single life in a population-controlled society where only one child and one child were allowed to go to the action film category. The novel material and actor Numi Lapas’s one-man seven-station acting attracted attention. Despite being a CGV solo release, he gained great popularity by leading’singing on the road’ with word of mouth at the time of release.

Details and reservations for the ‘Big Data Movie Recommendation’ exhibition are available on the CGV homepage and mobile app.

“CGV Lee Chun-Gil, Head of Data Strategy Team, said, “With CGV’s self-developed box office analysis and big data algorithms, we have bundled a movie that customers would like to see again in the theater and presented it to this exhibition. We will do our best to show various contents by analyzing and excavating with them.”

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