Automatic Recommendation Functions for IT Content Becoming Ubiquitous | Be Korea-savvy

Automatic Recommendation Functions for IT Content Becoming Ubiquitous


As mobile services whose contents need to be selectively displayed due to their relatively small screens are outdoing PC-related business, and the public’s interest in big data and AI (Artificial Intelligence) grows, the introduction of the technology has become even faster. (Image: Yonhap)

As mobile services whose contents need to be selectively displayed due to their relatively small screens are outdoing PC-related business, and the public’s interest in big data and AI (Artificial Intelligence) grows, the introduction of the technology has become even faster. (Image: Yonhap)

SEOUL, Oct. 4 (Korea Bizwire) – Automatic recommendation systems, in which a machine analyzes a user’s interests and shows news articles, video-clips, music, and other items which suit his or her taste, are becoming ubiquitous. The function was unthinkable even a few years ago on domestic machines.

As mobile services whose contents need to be selectively displayed due to their relatively small screens are outdoing PC-related business, and the public’s interest in big data and AI (Artificial Intelligence) grows, the introduction of the technology has become even faster.

According to a source in the industry, Kakao was the main company that accelerated the introduction of automatic recommendation functions. It introduced a technology named Rubik to recommend news articles on the first page of the portal Daum in June 2015.

When this function was applied, the previous practice, in which editors select news articles and arrange them on the screen, was discarded. Users were able to directly see news tailored to their tastes.

Kakao’s automatic recommendation technology is being applied to its many other affiliated platforms including Kakao Channel (a content service for Kakao Talk), Kakao TV, and Kakao Page (a web novel and cartoon service).

Its rival, Naver introduced AiRS, an automatic recommendation system to its news service in February of this year, and is advancing a plan to apply relevant technologies to other areas.

A pay web cartoon platform, Lezhin Comics, also recently jumped on the bandwagon of employing the automatic recommendation system.

Last month, it started its ‘For You’ service on the basis of machine learning technology, which analyzes a user’s preference for particular cartoon types and selects one for him or her.

“The automatic recommendation system enables people to be exposed to more diverse content, unlike the era when an identical play list was shown to the public. The popularity of the automatic recommendation function will continue to rise with the strength of expanding contact points between content and consumers,” forecast an official in the IT industry.

 Ashley Song (ashley@koreabizwire.com)

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