This article details an end‑to‑end AI system that replaces manual, error‑prone tagging of customer dialogues with a large‑language‑model‑driven, vector‑based pipeline that automatically discovers, clusters, and iteratively refines business‑level tags, dramatically cutting cycle time and improving coverage.
This article reviews OneID as a core data‑identity infrastructure for enterprise digital transformation, detailing its definition, origins, key use cases, technical and engineering challenges, and emerging trends such as CDP adoption, enterprise‑wide deployment, and weak‑ID intelligent association.
This article provides an in‑depth overview of user profiling, covering its definition, objectives, data dimensions, tagging taxonomy, technical architecture, data processing pipelines using Hadoop, Spark, Hive, MongoDB and MySQL, as well as practical challenges and best‑practice steps for building scalable profiling systems.
This article demonstrates a step‑by‑step workflow for constructing a churn prediction model using R in Discover, covering data loading, preprocessing, feature extraction, labeling, random‑forest training, prediction, and evaluation to help businesses proactively retain high‑value customers.
