Language: | Slovenian |
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Year of publishing: | 2023 |
Typology: | 2.11 - Undergraduate Thesis |
Organization: | UL FRI - Faculty of Computer and Information Science |
Publisher: | [E. Calcina] |
UDC: | 004.85:81'322(043.2) |
COBISS: |
163762435
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Views: | 8 |
Downloads: | 1 |
Average score: | 0 (0 votes) |
Metadata: |
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Secondary language: | English |
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Secondary title: | Event-based news clustering |
Secondary abstract: | In the modern world, we daily face a flood of news. For easier searching, it is useful if the news are grouped according to related events. In the thesis, we present a methodology for clustering news by events. The methodology combines the use of text embeddings, a clustering algorithm and news filtering methods. We tested the methodology on a dataset of online news and evaluated it statisticaly and manualy. The results indicate that the news clusters primarily depict the same events. However, higher accuracy is accompanied by a substantial amount of non-clustered news. |
Secondary keywords: | news;events;machine learning;news clustering;event detection;language model;computer science;diploma;Računalniško jezikoslovje;Strojno učenje;Računalništvo;Univerzitetna in visokošolska dela; |
Type (COBISS): | Bachelor thesis/paper |
Study programme: | 1000470 |
Thesis comment: | Univ. v Ljubljani, Fak. za računalništvo in informatiko |
Pages: | 23 str. |
ID: | 19904923 |