graph networks | BestHub

DataFunSummit

Sep 12, 2022 · Artificial Intelligence

Graph Network Data in Trend‑Driven Video Production on Kuaishou: Concepts, Applications, and Frequency Illusion

This article explains the fundamentals of graph networks, their use in Kuaishou’s short‑video ecosystem for community detection, trend‑driven content creation, and causal inference, and describes how key network nodes and frequency‑illusion effects are leveraged to boost user engagement and content virality.

Kuaishoucausal inferencefrequency illusion

0 likes · 14 min read

Graph Network Data in Trend‑Driven Video Production on Kuaishou: Concepts, Applications, and Frequency Illusion

DataFunSummit

May 5, 2022 · Artificial Intelligence

Advertising Targeting: Pain Points, Audience Insight System, Relationship Network Applications, and Modeling Strategies

The article examines the challenges advertisers face in a monopolized traffic environment, presents a three‑layer audience insight system, explores graph‑based relationship network methods, and discusses various modeling approaches—including single‑stage, cross‑stage, and multi‑task learning—along with practical considerations for data security and platform integration.

AIData Scienceadvertising

0 likes · 11 min read

Advertising Targeting: Pain Points, Audience Insight System, Relationship Network Applications, and Modeling Strategies

DataFunTalk

Feb 20, 2019 · Artificial Intelligence

Recommendation Reasoning and Its Path Toward Future AI

This article explores why recommendation systems need reasoning, how recommendation reasoning connects to future strong AI, discusses explainability, causal inference, graph-based reasoning, and the philosophical underpinnings of AI, while also reflecting on practical examples from Hulu's recommendation platform.

causal reasoningexplainable AIfuture AI

0 likes · 25 min read

Recommendation Reasoning and Its Path Toward Future AI