PRINCE-Reference-Cited by-同舟云学术

PRINCE

Published:2020-01-20 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 13th International Conference on Web Search and Data Mining
language:
Short-container-title:

Author:

Ghazimatin Azin¹,Balalau Oana²,Saha Roy Rishiraj¹,Weikum Gerhard¹

Affiliation:

1. Max Planck Institute for Informatics, Saarbruecken, Germany

2. Inria and École Polytechnique, Palaiseau, France

Funder

DFG Collaborative Research Center 1223

ERC Synergy Grant (imPACT)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3336191.3371824

Reference59 articles.

1. Qingyao Ai Vahid Azizi Xu Chen and Yongfeng Zhang. 2018. Learning heterogeneous knowledge base embeddings for explainable recommendation. Algorithms 11 9 (2018). Qingyao Ai Vahid Azizi Xu Chen and Yongfeng Zhang. 2018. Learning heterogeneous knowledge base embeddings for explainable recommendation. Algorithms 11 9 (2018).

2. Reid Andersen Christian Borgs Jennifer Chayes John Hopcraft Vahab S Mirrokni and Shang-Hua Teng. 2007. Local computation of PageRank contributions. In WAW. Reid Andersen Christian Borgs Jennifer Chayes John Hopcraft Vahab S Mirrokni and Shang-Hua Teng. 2007. Local computation of PageRank contributions. In WAW.

3. Reid Andersen Fan Chung and Kevin Lang. 2006. Local graph partitioning using Pagerank vectors. In FOCS. Reid Andersen Fan Chung and Kevin Lang. 2006. Local graph partitioning using Pagerank vectors. In FOCS.

4. Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient

5. Bahman Bahmani Abdur Chowdhury and Ashish Goel. 2010. Fast incremental and personalized PageRank. In VLDB. Bahman Bahmani Abdur Chowdhury and Ashish Goel. 2010. Fast incremental and personalized PageRank. In VLDB.

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