Thesis supervisor: András id. Benczúr
Location of studies (in Hungarian): ELTE, Faculty of Informatics Abbreviation of location of studies: ELTE
Description of the research topic:
The past fifteen years have seen an extensive development of communication network infrastructures, a vast spread of physical objects embedded with sensors, software, and network-connectivity, and the accompanying digitization of every aspect of human life and business, for example, operations, manufacturing, finance, marketing, health, and leisure, to name only a few. Nowadays, powerful computers and new technologies are available for storing and processing huge amounts of data, even in real time. The convergence of these developments has given rise to the formation of data-centric business applications, which combine multiple data sources to create models in order to provide new insights about the examined activities and processes (e.g. business, manufacturing), detect anomalous behaviours, predict various parameters and recommend items, products to customers.
This PhD topic focuses on challenges of fields that – due to the lack of significant amount of data – have not been solved yet. The work will primarily deal with the analysis of mass data in various application areas:
• Customer experience analysis and prediction in the telecommunication and other domains
• Fraud management and anomaly detection in novel telecommunication services
• Smart Cities & M2M – Analysis of open city platform and IoT data for smarter cities
• Societal Challenges including health, disaster and environment management
After the identification of domain-specific analytical problems the PhD student will build novel data mining and machine learning methods and models to address the given problems.
Required language skills: English Number of students who can be accepted: 2
Deadline for application: 2018-05-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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