EDBT 2026 Demo / reviewers in the wild / expert
Punam Bedi
dblp:25/4147
· DBLP profile ↗
6ranked-venue papers in the field
2as first author
4since 2021 · last 2026
0000-0002-6007-7961ORCID · corroborated
Domains — venue-derived; a paper can count in several
Knowledge Engineering, Semantic Web & Information Systems · 4 (1 first)Data Mining & Knowledge Discovery · 2 (1 first)
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | A contextual bandits framework using Siamese architecture for group reciprocal recommendations
Tulika Kumari, Bhavna Gupta, Ravish Sharma, Punam Bedi |
Knowl. Inf. Syst. | 4 |
| 2025 | XLR-KGDD: leveraging LLM and RAG for knowledge graph-based explainable disease diagnosis using multimodal clinical information
Punam Bedi, Anjali Thukral, Shivani Dhiman |
Knowl. Inf. Syst. | 1 |
| 2024 | Session-aware recommender system using double deep reinforcement learning
Purnima Khurana, Bhavna Gupta, Ravish Sharma, Punam Bedi |
J. Intell. Inf. Syst. | 4 |
| 2022 | A contextual-bandit approach for multifaceted reciprocal recommendations in online dating
Tulika Kumari, Ravish Sharma, Punam Bedi |
J. Intell. Inf. Syst. | 3 |
| 2014 | Empowering recommender systems using trust and argumentation
Punam Bedi, Pooja Bhatt Vashisth |
Inf. Sci. | 1 |
| 2012 | Building Socially-Aware E-Learning Systems Through Knowledge ManagementabstractConformance to social context while designing an e-learning course is crucial in enhancing acceptability of the course. Building socially aware e-learning courses requires elicitation of social opinion from various stakeholders associated with the system. Stakeholders are disparate in their perception towards the intricacies of the system, leading to generation of numerous assorted ideas. Knowledge Management (KM) assimilates these ideas to bring congruency into the system. This paper proposes i) a model KMeLS (Knowledge Management in e-Learning Systems) built upon the SECI (Socialization, Externalization, Combination and Internalization) framework, and ii) an algorithm PARSeL (Prioritizing Alternatives using Recommendations of Stakeholders in e-Learning) to incorporate KM into designing an e-learning course. PARSeL prioritizes the content using stakeholder recommendations using Analytic Hierarchy Process (AHP) and fuzzy modeling. A case study is also presented with a goal of prioritizing a set of programming languages for an online computing course. The proposed methodology can be promising in recommending appropriate content for the e-learners and can be implemented to benefit e-learning organizations in a wider spectrum. Hema Banati, Punam Bedi |
Int. J. Knowl. Manag. | 3 |