DATA LABS Sticker Data Labs Ad Manga Music Live News > Independent from service/dev depts. > Aggregate data across various services > Provide analysis/solution from data across various services
> Collection of users' behavioral logs across various LINE services Z-FEATURES OVERVIEW Transform into structures that cover about 80% of all ML use cases
Y-FEATURES USER DEMOGRAPHICS ESTIMATION FOR JP REGION TRAINING TIME (RELATIVE TO Z-FEATURES) 0 0.25 0.5 0.75 1 gender age-group region 0.06 0.02 0.05 PREDICTION TIME (RELATIVE TO Z-FEATURES) 0 0.25 0.5 0.75 1 gender age-group region 0.52 0.51 0.20
C-FEATURES OVERVIEW > Embedding of each service's contents > Currently available for two services • News articles: SCDV with fastText • Sticker images: Xception
HOW WE USE FEATURES AT DATA LABS > Feature as a Service • Achieve data standardization/democratization • Improve development efficiency > Available Features • User features • Obfuscated user features • Content features