NOUS: Construction and Querying of Dynamic Knowledge Graphs
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Abstract (arXiv)
The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a transformative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowledge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queries where the answer is embedded across multiple data sources.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Jun 2016.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 1; 2026: 1.
6 papers.
- 2022Neural Graph Databasescited by 11
- 2023HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformerscited by 10
- 2024Demystifying Higher-Order Graph Neural Networkscited by 4
- 2024Self-sustaining Software Systems (S4): Towards Improved Interpretability and Adaptationcited by 2
- 2026GraphSeek: Next-Generation Graph Analytics with LLMscited by 1
- 2025Higher-Order Graph Databasescited by 0
- 2026GraphSeek: Next-Generation Graph Analytics with LLMs11 Feb 2026
- 2025Higher-Order Graph Databases24 Jun 2025
- 2024Demystifying Higher-Order Graph Neural Networks18 Jun 2024
- 2024Self-sustaining Software Systems (S4): Towards Improved Interpretability and Adaptation21 Jan 2024
- 2023HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers30 Nov 2023
- 2022Neural Graph Databases20 Sep 2022