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Neuro-Symbolic AI Research as part of RAI Group @ Hull

We are one of the very few research groups in the country to research into Neuro-Symbolic Artificial Intelligence. We have over 15+ years of track record in the development of Knowledge graph-based approaches to exploit the potential of knowledge-infused techniques in a range of domains including health, circular economy, net zero, cyber security, law and many other domains. 


Neuro-symbolic artificial intelligence(NS-AI) refers to a field of research and applications that combines machine learning methods based on artificial neural networks, such as deep learning, with symbolic approaches to computing and artificial intelligence (AI), as can be found for example in the AI subfield of knowledge representation and reasoning. Neuro-symbolic artificial intelligence can be defined as the subfield of artificial intelligence (AI) that combines neural and symbolic approaches.


By neural we mean approaches based on artificial neural networks – sometimes called connectionist or subsymbolic approaches – and in particular this includes deep learning, which has provided very significant breakthrough results in the last decade, and is fuelling the current general interest in AI. By symbolic, we mean approaches that rely on the explicit representation of knowledge using formal languages – including formal logic – and the manipulation of language items (‘symbols’) by algorithms to achieve a goal.

Our focus in NS-AI is:

-Advancing techniques to build and manage knowledge graph structures

-Navigation and exploration of knowledge graph structures

-Use of knowledge graph-based knowledge-infused techniques to improve performance of Large Language models: for improving explainability, factuality, and address: hallucinations, recencyand application-level safety


Numerous members of our group actively contribute to advancing research in this field, and several PhD students have successfully completed their programs under our guidance. Below is a list of publications resulting from our research in NS-AI.

Selected Publications:


  • Al-Tawil, Marwan; Dimitrova, Vania; Thakker, Dhavalkumar; Abu-Salih, Bilal; Emerging Exploration Strategies of Knowledge Graphs, IEEE Access,2023

  • Mboli, Julius Sechang; Thakker, Dhavalkumar; Mishra, Jyoti L; An Internet of Things‐enabled decision support system for circular economy business model, Software: Practice and Experience,52,3,772-787,2022

  • Mboli, Julius; Thakker, Dhavalkumar; Mishra, Jyoti; Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models. 25th International Conference on Enterprise Information Systems,2023.

  • Mboli, Julius; Thakker, Dhavalkumar; Mishra, Jyoti; Sivrajah, Sankar; Domain Experts and Natural language Processing in the Evaluation of Circular Economy Business Model Ontology, The Sixth International Workshop on Semantic Computing and Knowledge Creation based on Needs Engineering as part of 15th IEEE International Conference on ​Semantic Computing,2021.

  • Aljamel, Abduladem; Osman, Taha; Thakker, Dhavalkumar; A semantic knowledge-based framework for information extraction and exploration, International Journal of Decision Support System Technology (IJDSST),13,2,85-109,2021, IGI Global

  • Thakker, Dhavalkumar; Mishra, Bhupesh Kumar; Abdullatif, Amr; Mazumdar, Suvodeep; Simpson, Sydney; "Explainable artificial intelligence for developing smart cities solutions, Smart Cities Journal,3,4,1353-1382,2020.

  • Thakker, Dhavalkumar; Patel, Pankesh; Intizar, Ali; Shah, Tejal; Semantic Web of Things for Industry 4.0,IOS Semantic Web Journal,11,6,2020, IOS. 

  • Phengsuwan, Jedsada; Shah, Tejal; Sun, Rui; James, Philip; Thakker, Dhavalkumar; Ranjan, Rajiv; ", Ontology-based System for Discovering Landslide Induced Emergency in Electrical Grid, Transactions on Emerging Telecommunications Technologies,2020.

  • Dimitrova, Vania; Mehmood, Muhammad Owais; Thakker, Dhavalkumar; Sage-Vallier, Bastien; Valdes, Joaquin; Cohn, Anthony; ",An Ontological Approach for Pathology Assessment and Diagnosis of Tunnels,Elsevier Journal of Engineering Applications of Artificial Intelligence,2020,Elsevier

  • Phengsuwan, Jedsada; Balan, Nipun; Sun, Rui; Shah, Tejal; James, Philip; Thakker, Dhavalkumar; Pullarkatt, Divya; Hemalatha, T; Vinodini Ramesh, Maneesha; Ranjan, Rajiv; ",Context-based Knowledge Discovery and Querying for Social Media Data,IEEE 20th International Conference on Information Reuse and Integration for Data Science,2019.

  • Thakker, Dhavalkumar; Schwabe, Daniel; García, Roberto; Kozaki, Kouji; Brambilla, Marco; Dimitrova, Vania; A Note on Intelligent Exploration of Semantic Data,"Semantic Web – Interoperability, Usability, Applicability", 2019, IOS Press Journal

  • Al-Tawil, Marwan; Dimitrova, Vania; Thakker, Dhavalkumar; ", Using Knowledge Anchors to Facilitate User Exploration of Data Graphs, "Semantic Web – Interoperability, Usability, Applicability",2018, IOS Press Journal

  • Al-Tawil, Marwan; Dimitrova, Vania; Thakker, Dhavalkumar; Poulovassilis, Alexandra; ", Evaluating knowledge anchors in data graphs against basic level objects," Web Engineering: 17th International Conference, ICWE 2017, Rome, Italy, June 5-8, 2017, 3-22,2017, Springer International Publishing

  • Ranjan, Rajiv; Thakker, Dhavalkumar; Armin, Haller.; Buyya, R; ",A Note on Exploration of IoT generated Big Data using Semantics,Elsevier  Journal of Future Generation Computer Systems (FGCS),2017,Elsevier

  • Thakker, Dhavalkumar; User Interaction with Linked Data: An Exploratory Search Approach, International Journal of Distributed Systems and Technologies (IJDST),7,1,79-91,2016.

  • Al-Tawil, Marwan; Dimitrova, Vania; Thakker, Dhavalkumar; Bennett, Brandon; ", Identifying Knowledge Anchors in a Data Graph, Hypertext 2016, ACM. 

  • Patel, Pankesh; Gyrard, Amelie; Thakker, Dhavalkumar; Sheth, Amit; Serrano, Martin; SWoTSuite: A Toolkit for Prototyping Cross-domain Semantic Web of Things Applications, International Semantic Web Conference (ISWC 2016), Springer

  • Thakker, Dhavalkumar; Karanasios, Stan; Blanchard, Emmanuel; Lau, Lydia; Dimitrova, Vania; Ontology for Cultural Variations in Interpersonal Communication: Building on Theoretical Models and Crowdsourced Knowledge, Journal of the Association for Information Science and Technology(JASIST),2016, Wiley. 

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