Summary of Text2cypher: Bridging Natural Language and Graph Databases, by Makbule Gulcin Ozsoy et al.
Text2Cypher: Bridging Natural Language and Graph Databases
by Makbule Gulcin Ozsoy, Leila Messallem, Jon Besga, Gianandrea Minneci
First submitted to arxiv on: 13 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, researchers introduce a novel approach called Text2Cypher that enables non-experts to efficiently interact with knowledge graphs using natural language queries. This is achieved by translating user-inputted text into Cypher query language, thereby bridging the gap between domain experts and those without specialized knowledge of Cypher. The proposed solution leverages knowledge graphs’ ability to represent complex data structures while making it accessible to a broader audience. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes it possible for people without technical expertise to work with complex data using natural language queries. The scientists created a tool called Text2Cypher that translates what you say into the Cypher query language, which is used in special databases that store knowledge graphs. This means more people can use these powerful tools without needing years of training. |
