A programmatic introduction to Neo4j

By J. Webber. ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity, 2018

386 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/4cee38d9d088cf021bc5f5b9fda6764feeb1806a

How researchers see this paper

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

In Computer Networks and Communications

1. Zhaojiang Lin
2. Zihan Liu
3. Hao Peng
4. Andrea Madotto
5. Pascale Fung
6. Samuel Cahyawijaya
7. Genta Indra Winata
8. Yan Xu

In Computer Vision and Pattern Recognition

1. Pascale Fung
2. Zhaojiang Lin
3. Zihan Liu
4. Xindong Wu
5. Hao Peng
6. Lingfeng Zhong
7. Qian Li
8. Jia Wu

In Hardware and Architecture

1. Zhaojiang Lin
2. Zihan Liu
3. Andrea Madotto
4. Pascale Fung
5. Samuel Cahyawijaya
6. Genta Indra Winata
7. Yan Xu

Citations in the corpus

• Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems (2020, methodology): “, 2019) with CYPHER syntax (Webber, 2012), where the nodes are the requested information in R, and the labeled edges the constrains in C.”
• A Comprehensive Survey on Automatic Knowledge Graph Construction (2023, background): “Neo4j[350] is a lightweight NoSQL-based graph database that supports embedded dynamic knowledge graph storage.”