interest graph | BestHub

DataFunSummit

Aug 3, 2021 · Artificial Intelligence

Content Understanding for Personalized Recommendation: Interest Graph, Concept Mining, and Semantic Matching at Tencent

The article explains how Tencent addresses the limitations of traditional content understanding methods in personalized recommendation by introducing an interest‑graph framework that combines classification, concept, entity, and event layers, and details the associated mining, matching, and online evaluation techniques.

Content UnderstandingEmbeddingNLP

0 likes · 13 min read

Content Understanding for Personalized Recommendation: Interest Graph, Concept Mining, and Semantic Matching at Tencent

Qunar Tech Salon

Feb 6, 2020 · Artificial Intelligence

Content Understanding for Personalized Feed Recommendation: From Classification to Interest Graphs

The article explains how Tencent tackles content understanding in feed recommendation by evolving from traditional classification, keyword, and entity methods to a multi‑layer interest graph that captures concepts and events, addressing the need for full context, reasoning about user intent, and improving online performance.

AIContent UnderstandingEmbedding

0 likes · 12 min read

Content Understanding for Personalized Feed Recommendation: From Classification to Interest Graphs

DataFunTalk

Dec 2, 2019 · Artificial Intelligence

Content Understanding for Personalized Feed Recommendation: Interest Graph and Techniques

This article explains how Tencent tackles content understanding for personalized feed recommendation by combining traditional classification, keyword, and entity methods with deep learning embeddings, introducing an interest graph composed of taxonomy, concept, entity, and event layers to capture full context and infer user consumption intent.

Content UnderstandingEmbeddingNLP

0 likes · 14 min read