A Distributed Graph Engine for Web Scale RDF Data

By Kai Zeng, Jiacheng Yang, Haixun Wang, Bin Shao, Zhongyuan Wang. Proceedings of the VLDB Endowment, 2013

346 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/6d8fefb7cd96ab2f3ec841339675c3316675b404

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Bin Shao
2. Haixun Wang
3. Yatao Li
4. Kian-Lee Tan
5. Beng Chin Ooi
6. Meihui Zhang
7. Hao Zhang
8. Gang Chen

In Computer Networks and Communications

1. Kian-Lee Tan
2. Bin Shao
3. Beng Chin Ooi
4. Meihui Zhang
5. Haixun Wang
6. Yatao Li
7. Hao Zhang
8. Gang Chen

Citations in the corpus

• Trinity: a distributed graph engine on a memory cloud (2013, background): “Figure 14 (a) shows the response time of subgraph match queries on two real-life graphs (Wordnet and US patent network), while (b) shows the response time of four SPARQL queries on a LUBM RDF data set [20] with 1,367,122,031 triples [36].”
• In-Memory Big Data Management and Processing: A Survey (2015, background): “, a predicate) such that it can be extended to an RDF store [263], with both local predicate”