GIANT: Scalable Creation of a Web-scale Ontology
Summary: GIANT constructs a scalable, web-scale Attention Ontology from user attention signals, covering entities, concepts, events and topics. GNN-based mining over web docs and click graphs yields a hierarchical, phrase-rich ontology, deployed at Tencent with CTR gains in news recommendations. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Bang Liu
- 2. Weidong Guo
- 3. Di Niu
- 4. Jinwen Luo
- 5. Chaoyue Wang
- 6. Zhen Wen
- 7. Yu Xu
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,068 | Probase: A Probabilistic Taxonomy for Text Understanding | 2012 | SIGMOD | 0.00014316508 |
| 2,221 | Introduction to Recommender Systems | 2008 | SIGMOD | 9.2598933e-05 |
| 3,293 | Biperpedia: An Ontology for Search Applications | 2014 | VLDB | 7.2598242e-05 |
| 5,531 | Towards the Web of Concepts: Extracting Concepts from Large Datasets | 2010 | VLDB | 5.4562198e-05 |
| 7,913 | Mining Quality Phrases from Massive Text Corpora | 2015 | SIGMOD | 4.6139203e-05 |
| 8,290 | Modern Recommender Systems: from Computing Matrices to Thinking with Neurons | 2018 | SIGMOD | 4.5392079e-05 |
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