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Razvoj odprtokodnega ogrodja za obdelavo naravnega jezika
ID Krištofelc, Miha (Author), ID Žitnik, Slavko (Mentor) More about this mentor... This link opens in a new window

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Abstract
V diplomskem delu se bomo osredotočili na razvoj aplikacije za gradnjo cevovodov z namenom obdelave naravnega jezika. Naš cilj je raziskati trenutne rešitve na trgu in vključiti izboljšave v razvoj nove aplikacije, prilagojene raziskovalcem in splošni javnosti, ki jo zanima ONJ. Za preverjanje uporabnosti aplikacije bomo izvedli uporabniško testiranje, funkcionalno testiranje ter tudi testiranje zmogljivosti. Pri razvoju aplikacije bomo uporabili ustrezna razvojna orodja, kot so Django za razvoj zalednega dela, NextJS za razvoj čelnega dela in Docker za upravljanje z vsebniki. Poleg tega bomo za nadzor različic in varnostno kopiranje kode uporabljali program Git. V zaključku bomo predstavili ocene uporabniške izkušnje, oceno učinkovitosti aplikacije in splošne rezultate diplomskega dela.

Language:Slovenian
Keywords:cevovodi, obdelava naravnega jezika, docker, vsebniki, podatkovni inženiring
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2024
PID:20.500.12556/RUL-161491 This link opens in a new window
COBISS.SI-ID:212611331 This link opens in a new window
Publication date in RUL:11.09.2024
Views:164
Downloads:296
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Secondary language

Language:English
Title:Development of an open source framework for natural language processing
Abstract:
In thesis, we will focus on the development of a pipeline application for natural language processing. Our aim is to explore current solutions on the market and incorporate improvements into the development of a new application tailored to researchers and the general public interested in NLP. To verify the usability of the application, we will perform user testing, functional testing as well as performance testing. In developing the application we will use appropriate development tools such as Django for backend development, NextJS for frontend development and Docker for container management. In addition, we will use Git for version control and code backup. In conclusion, we will present the user experience evaluations, the performance evaluation of the application and the overall results of the thesis.

Keywords:Pipelines, Natural language processing, Docker, Containers, Data engineering

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