Mobile Game Company Bagel Code Adopts User Behavior Prediction Paper at International Web Conference
Feb 18, 2025
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The international web conference began in 1994 and is the most prestigious academic conference in the web field where cutting-edge research such as web, data mining, and artificial intelligence is shared, with 281 papers submitted to the Industrial Track this year, of which only 63 were finally selected.
BagelCode has demonstrated its AI technology through deep learning based LTV prediction model (MDLUR) in KDD in 2023. The study presents a methodology for simultaneously predicting user lifetime value (LTV) and whether to leave for a specific period by applying a more advanced data relationship expansion technique, the company said.
The Bagel Code Data & AI team emphasized that they elaborated the model by categorizing user behavior data to identify interrelationships and focused on improving predictive performance and strengthening model interpretation. In addition, the research results are applied to practical use to predict advertising performance early and analyze the propensity of new users. In particular, it added that the forecast time of the return on advertising investment (based on ROAS, D7) was reduced by 85.7% and the forecast accuracy improved by 37.2%.
Bagel Code emphasized that it is building a data ecosystem that leads to research, technology development, and data accumulation through thorough experiments and verification. It also said that it plans to optimize the service environment and strengthen customized operations through continuous advancement of predictive models in the future.
"Following the last paper, this adoption is also the result of Bagel Code's continuous investment in AI technology research and efforts to improve data-driven services. We will continue to increase technological competitiveness and maintain balanced growth through organic linkage between academia and industry." said Kim Joo-hyun, general director of Bagel Code Data & AI.
This article was translated by Naver AI translator.
