Ina Naydenova

Dr. Ina Naydenova


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2024 in AIP Conference Proceedings
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Conference Paper
Closed access
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KKKalinka Kaloyanova
Kalinka Kaloyanova
Zlatinka Svetoslavova KovachevaZlatinka Svetoslavova Kovacheva
Zlatinka Svetoslavova Kovacheva
INIna Naydenova
Ina Naydenova
The secondary use of data concerns the use of data for purposes that are different from the purpose for which data was initially collected. Although data manage The secondary use of data concerns the use of data for purposes that are different from the purpose for which data was initially collected. Although data manage

16 May 2011
Verified
Book Chapter
Closed access
PDF file
KKKalinka Kaloyanova
Kalinka Kaloyanova
INIna Naydenova
Ina Naydenova

1 January 2023 in AIP Conference Proceedings
Verified
Conference Paper
Open access
PDF file
INIna Naydenova
Ina Naydenova
Zlatinka Svetoslavova KovachevaZlatinka Svetoslavova Kovacheva
Zlatinka Svetoslavova Kovacheva
KKKalinka Kaloyanova
Kalinka Kaloyanova
Data warehouses are a widespread tool for data processing. The article explores different points of view and expectations of the stakeholders of modern data war

15 May 2026 in Future Internet
Verified
Journal Article
Open access
PDF file
INIna Naydenova
Ina Naydenova
Zlatinka Svetoslavova KovachevaZlatinka Svetoslavova Kovacheva
Zlatinka Svetoslavova Kovacheva
IGIliya Krasimirov Georgiev
Iliya Krasimirov Georgiev
User interface evaluation remains fragmented across performance metrics, subjective assessments, and user-dependent factors, limiting the comparability and interpretability of results across methodological traditions. This paper proposes a multidimensional evaluation framework that integrates these perspectives into a coherent analytical structure. The framework consists of three dimensions—Functional–Objective, Cognitive–Perceptual, and Contextual–Individual—each capturing a distinct facet of interface quality. A key feature of the proposed approach is the use of profile-dependent weighting, which enables evaluation results to reflect the specific priorities of different user groups. The framework’s operational logic is demonstrated through structured illustrative scenarios, showing how the model can be applied in practice to support more informed design and evaluation decisions. By aligning heterogeneous evaluation logics within a unified structure, the proposed approach provides a systematic basis for more consistent, transparent, and context-sensitive assessment of user interfaces.