Mar 24, 2019   5:37 p.m. Gabriel
Academic information system

Summary of topics offered - Faculty of Electrical Engineering and Information Technology


Basic information

Type of work: Diploma thesis
Topic: Efektívne hľadanie vo finančných dátach
Title of topic in English: Efficient searching in finance data
State of topic: approved (prof. Dr. Ing. Miloš Oravec - Study programme supervisor)
Thesis supervisor: Privatdozent Dr. rer. nat. Martin Drozda
Faculty: Faculty of Electrical Engineering and Information Technology
Supervising department: Institute of Computer Science and Mathematics - FEEIT
Max. no. of students: 1
Academic year:2018/2019
Proposed by: Privatdozent Dr. rer. nat. Martin Drozda
Summary: Cieľom tejto diplomovej práce je návrh, analýza a testovanie algoritmov pre efektívne hľadanie vo finančných dátach. Ďalším cieľom je implementácia vhodného webového rozhrania pre zvolený algoritmus. Literatúra: Jin Shieh and Eamonn Keogh. iSAX: indexing and mining terabyte sized time series. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '08), 2008. ACM, New York, NY, USA, 623-631. DOI: https://doi.org/10.1145/1401890.1401966



Limitations of the topic

To sign up for a topic it is necessary to fulfil one of the following restrictions

Limit to study programme
The table shows limitations of study programme, field, track the student has to be enrolled in to be able to register for a given topic.

ProgrammeTrackTrack
I-API Applied Informatics-- not entered -- -- not entered --

Limit to courses
The table shows limitations of a course the student has to complete to be able to register for a given topic.

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