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Sledenje razvoju raziskovalnih tematik
DEBENJAK, MIHA (Author), Curk, Tomaž (Mentor) More about this mentor... This link opens in a new window

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Abstract
Spremljanje raziskovalnih tematik znanstvenih objav skupine raziskovalcev je zanimivo in hkrati pomembno za razumevanje razvoja nekega znanstvenega področja in raziskovalcev, ki delujejo na področju. Raziskovalci se ukvarjajo z različnimi področji, zato se tudi teme, o katerih pišejo v znanstvenih objavah, razlikujejo. Na podlagi besed, ki so uporabljene v znanstvenih člankih, lahko določimo teme, o katerih raziskovalci razpravljajo. V diplomski nalogi je opisano pridobivanje podatkov o člankih, njihova analiza in modeliranje tem člankov. Izvedena je bila tudi analiza o zastopanosti različnih tem skozi čas, kar nam pove o aktualnosti tem v določenem času. Zgrajen sistem smo uporabili za analizo publikacij Fakultete za računalništvo in informatiko Univerze v Ljubljani.

Language:Slovenian
Keywords:modeliranje tem, model LDA, rudarjenje besedil, vizualizacija, razvoj tematik, obdelava naravnega jezika
Work type:Bachelor thesis/paper (mb11)
Organization:FRI - Faculty of computer and information science
Year:2019
COBISS.SI-ID:1538354371 Link is opened in a new window
Views:439
Downloads:116
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Secondary language

Language:English
Title:Tracking research topics
Abstract:
Following the research topics of the scientific publications of a group of researchers is interesting and at the same time important for understanding the development of a scientific field and researchers working in it. The researchers do not work in the same field, therefore the topics of their work differ. Topics of the articles can be identified on the basis of words used. The thesis describes the acquisition of data on articles, their analysis and modelling of topics that they discuss. In addition, an analysis was conducted on the representation of different topics over time, which shows most frequently discussed topics in certain time periods. This system was used for the analysis of publications of the Faculty of Computer and Information Science of the University of Ljubljana.

Keywords:topic modeling, LDA model, text mining, visualization, topic development, natural language processing

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