Durgesh Nandini

dblp:178/1755 · DBLP profile ↗
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9ranked-venue papers
5as first author
6since 2021 · last 2025
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 5 · 3 first-author · 4 since 2021Artificial intelligence and machine learning · 3 · 2 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 2 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2025 Organising Knowledge from Text: Prompt-Based Triple Extraction and Graph Enrichment with Large Language Models
Durgesh Nandini, Simon Bloethner, Mario Larch, Mirco Schönfeld
TPDL1
2025 Towards Structured Knowledge: Advancing Triple Extraction from Regional Trade Agreements Using Large Language Models
Durgesh Nandini, Rebekka Koch, Mirco Schönfeld
ICWE1
2025 DHOW '25: 2nd International Workshop on Diffusion of Harmful Content on Online Web
abstract
With the advancement of digital technologies and gadgets, online content has become easily accessible. At the same time, harmful content also spread widely. There are different harmful content types present on various platforms in multiple languages. The topic of harmful content is broad and covers multiple research directions. Users of platforms are affected by all of them. In research, the different forms are mostly analysed separately, e.g. misinformation, cyber-bullying and hate speech. Most research has been conducted for only one platform, for a monolingual situation or on a particular issue. Counter-measures like blocking are down-ranking can make harmful content spreaders to switch platforms and languages to continuously reach a user base. Harmful content does not only appear on social media but also on news media. Spreader share harmful content in posts, news articles, comments and hyperlinks. There is a great need to study harmful content across platforms, languages, and topics. We plan to bring the research on harmful content under one umbrella such that different approaches and novel methods can be shared. The workshop will also cover the currently ongoing issues of war and elections. We propose the workshop, DHOW: Diffusion of Harmful Content on Online Web, which brings together the research on different topics of harmful content. We expect to discuss innovative research work and future research directions. The proposed workshop is the next iteration of DHOW 2024. https://dhow-workshop.github.io previously organized at ACM WebSci 2024 in Stuttgart, Germany.
Amit Kumar Jaiswal 0001, Thomas Mandl 0001, Gautam Kishore Shahi, Durgesh Nandini, Haiming Liu 0002
ACM Multimedia4
2024 How to Surprisingly Consider Recommendations? A Knowledge-Graph-Based Approach Relying on Complex Network Metrics
Oliver Baumann, Durgesh Nandini, Anderson Rossanez, Mirco Schönfeld, Júlio Cesar dos Reis
KEOD2
2024 Multidimensional Knowledge Graph Embeddings for International Trade Flow Analysis
Durgesh Nandini, Simon Bloethner, Mirco Schönfeld, Mario Larch
KEOD1
2022 A Comparison of Resource Data Framework and Inductive Logic Programing for Ontology Development
Durgesh Nandini
IEA/AIE1
2018 Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks
Durgesh Nandini, Elisa Capecci, Lucien Koefoed, Ibai Lana, Gautam Kishore Shahi, Nikola K. Kasabov
ICONIP (1)1
2018 Analysis, Classification and Marker Discovery of Gene Expression Data with Evolving Spiking Neural Networks
Gautam Kishore Shahi, Imanol Bilbao, Elisa Capecci, Durgesh Nandini, Maria Choukri, Nikola K. Kasabov
ICONIP (5)4
2015 MOD: Metadata for Ontology Description and Publication
Biswanath Dutta, Durgesh Nandini, Gautam Kishore Shahi
Dublin Core Conference2