Concept Mining for Data Management

Authors

Swarupa Hardikar
HAN University of Applied Sciences image/svg+xml , Radboud University Nijmegen image/svg+xml

Synopsis

The PhD project addresses data ambiguity, a core issue hampering the management of organisational data, and aims to support data management through concept mining. We intend to (semi-)automatically analyse perceived meanings of terms and concepts within an organisation’s data domain to aid terminological disambiguation. The concept mining system will deploy text mining and information retrieval techniques within unstructured data. We adopt a 3-phase approach of exploring the problem and requirements, iterative development and testing, and finally, an extrinsic evaluation in a real-life setting. Every component of the system will be intrinsically evaluated with metrics best suited to that component. The toolkit will also be evaluated qualitatively through studies with data managers for efficiency, quality and real-world applicability. The project will bridge the gap between domain expertise and automated methodologies, with expected contributions such as an evaluation framework for concept mining and advancement towards the research of terminology extraction.

Author Biography

Swarupa Hardikar, HAN University of Applied Sciences, Radboud University Nijmegen

I am a 2nd year PhD candidate at Radboud University (RU) and HAN University of Applied Sciences (where I also work as a junior researcher). I have a background in text mining, and my areas of interest include natural language processing, language modelling, information retrieval and data semantics. I am currently supervised by Prof.dr. Arjen de Vries (promoter, RU), Lec.dr. Stijn Hoppenbrouwers (co-promoter, HAN), and Dr. Maya Sappelli (daily supervisor, HAN).

Arnhem, the Netherlands. E-mail: swarupa.hardikar@han.nl 

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Published

June 5, 2026

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Hardikar, S. (2026). Concept Mining for Data Management. In D. Vidmar, A. Pucihar, M. Kljajić Borštnar, R. W. H. Bons, M. Glowatz, & H.-D. Zimmermann (Eds.), & (Ed.), 39th Bled eConference: Co-Creating Human-Centred and Responsible Digital Futures; Conference Proceedings (Vols. 39., pp. 1097-1108). University of Maribor Press. https://doi.org/10.18690/um.fov.4.2026.74