ponedeljek, 7. julij 2025 Anđela ĐUKIĆ:Application of Clustering-Based Recommendation Systems in Nursing Diagnosis in Pika POVH MAVRIČ: Understanding Customer Behavior Through Data Analytics in the Banking Sector
V ponedeljek, 7. julija 2025, bosta ob 16:00 uri izvedeni dve
predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.
ČAS/PROSTOR: 7. julij 2025 ob 16.00 prek Zoom-a (https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09).
1. predavanje:
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PREDAVATELJICA: Anđela ĐUKIĆ
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Anđela Đjukić is a second year Data Science Masters student at UP FAMNIT under the supervision of mentor Bošjan Žvanut and co-mentor Branko Kavšek. She is also a part of the GDI UP Project at FAMNIT.
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NASLOV: Application of Clustering-Based Recommendation Systems in Nursing Diagnosis
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POVZETEK:
This work explores how recommendation systems, specifically the CLUICE algorithm, can help with more efficient and accurate nursing diagnoses for older adults in a shorter amount of time.
The process of making a nursing diagnosis involves many steps and a lot of time and effort, specifically when connecting symptoms to possible diagnoses, and there aren’t many tools that help with this in an automated way.
With this in mind, as well as the basic recommendation system knowledge, patients are modeled as users and their symptoms as items, using ideas from recommendation systems commonly seen and used in domains like marketing. The aim is to investigate if a system like this can suggest nursing diagnoses via identifying patterns in symptom data, even when the information is incomplete or limited.
The further goal comes through applying an approach not traditionally used in healthcare, with the potential to enhance clinical decision-making and reduce the cognitive burden on practitioners.
Seminar bo potekal v angleškem jeziku.
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2. predavanje:
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PREDAVATELJICA: Pika POVH MAVRIČ
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Pika Povh Mavrič is currently completing her master’s studies in Computer Science at UP FAMNIT. She works as a data analyst in the Customer Relationship Management department at a bank, where she applies and deepens her expertise in data analytics. Her work involves automating processes, improving data quality, creating various reports and analyses, and applying data-driven decision-making to everyday processes within the department. The topic of her paper aligns well with her work in the banking sector.
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NASLOV: Understanding Customer Behavior Through Data Analytics in the Banking Sector
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POVZETEK:
This article examines how data analytics and machine learning are reshaping customer behavior analysis in the banking sector. It focuses on key applications such as credit scoring, fraud detection, churn prediction, and product recommendation, using models like Random Forest, LightGBM, and neural networks. The study highlights improved decision-making and customer engagement, while also addressing challenges around data quality, transparency, and ethics. It underscores the importance of organizational readiness and responsible AI practices to balance predictive accuracy with fairness and interpretability.
Seminar bo potekal v angleškem jeziku.
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Seminarja bosta izvedena online prek Zoom-a na sledeči povezavi:
https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09
