Samodejno prepoznavanje vsebinskih blokov znotraj spletišč

diplomsko delo

Mitja Brezovnik (Author), Slavko Žitnik (Mentor)

Abstract

Informacije so dandanes enostavno dostopne, informiranost pa ključnega pomena. S to mislijo smo se lotili izdelave rešitve, ki bo omogočala luščenje vsebine člankov iz slovenskih novičarskih portalov. Glavni problem s katerim se pri tovrstnih rešitvah soočimo je ločitev vsebine od nepotrebnih informacij, kot so oglasi, komentarji in ostali postavitveni elementi spletnih strani. Za rešitev tega problema smo ubrali pristop, ki temelji na značilnostih plitkih besedil. Na njegovi osnovi smo zasnovali jezikovni model, ki smo ga zgradili s pomočjo slovenskega korpusa 10000 slovenskih člankov iz 5 različnih novičarskih portalov. Končni izdelek predstavlja ekstraktor, ki omogoča pridobitev vsebine slovenskih člankov in jih predstavi v strukturirani obliki.

Keywords

ekstrakcija;članki;značilnosti plitkih besedil;računalništvo;računalništvo in informatika;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2021
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[M. Brezovnik]
UDC:	004(043.2)
COBISS:	50546435
Views:	655
Downloads:	93
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Automatic identification of content blocks from Web sites
Secondary abstract:	Nowadays information is easily accessible and even more so valuable. With this in mind, we set about creating a solution that will enable content extraction of articles found in Slovenian news portals. The main problem we face with such solutions is separating the content from unnecessary information, such as ads, comments and other layout elements of web pages. To solve this problem, we implemented a solution based on shallow text features. On its basis, we designed a language model, which was built with the help of Slovenian news corpus that contains 10000 articles from 5 different news portals. The final product is an extractor that allows content extraction of Slovenian articles and presents them in a structured form.
Secondary keywords:	extraction;articles;shallow text features;computer science;computer and information science;diploma;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000468
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	46 str.
ID:	12531405