magistrsko delo
Abstract
V tem delu se ukvarjamo s problemom ekstrakcije seznama oseb s poljubnega spletišča. V ta namen implementiramo spletnega pajka za identifikacijo potencialnih podstrani z osebami in ekstraktor podatkov, ki s poljubne spletne strani izvleče podatke o osebah.
Pokažemo, da osnovne metode, kot so primerjava imena s seznamom imen, ne dosežejo sprejemljive natančnosti. Pokažemo, da je analiza strukture seznama in prenos odkritega znanja ključna metoda za izboljšavo rezultatov do stopnje, kjer dosežemo sprejemljiv nivo natančnosti. S pomočjo tega pristopa smo izboljšali F1 mero za 50 % na razvojni in za 35 % na skriti testni množici.
Keywords
splet;ekstrakcija podatkov;avtomatska ekstrakcija podatkov s spleta;fokusirani spletni pajki;strukturirani podatki;nestrukturirani podatki;računalništvo in informatika;magisteriji;
Data
Language: |
Slovenian |
Year of publishing: |
2021 |
Typology: |
2.09 - Master's Thesis |
Organization: |
UL FRI - Faculty of Computer and Information Science |
Publisher: |
[M. Koplan] |
UDC: |
004.738.5(043.2) |
COBISS: |
83603971
|
Views: |
167 |
Downloads: |
27 |
Average score: |
0 (0 votes) |
Metadata: |
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Other data
Secondary language: |
English |
Secondary title: |
Automatic extraction of employee data from corporate websites |
Secondary abstract: |
In this work we tackle the problem of extracting lists of people from corporate websites. For this purpose we implement a web crawler to identify possible subpages with people and a data extractor, which is designed to work on any website.
We show that basic methods, such as matching names from a list, don't reach acceptable accuracy. We show that analysing the structure and transfrering the discovered knowledge of a list is crucial in reaching the required level of accuracy. Using this approach we have improved the score of our final results by 50 % in the development and by 35 % in the hidden test set. |
Secondary keywords: |
web;data extraction;automatic web data extraction;focused webcrawlers;structured data;unstructured data;computer science;computer and information science;master's degree;Spletna mesta;Računalništvo;Univerzitetna in visokošolska dela; |
Type (COBISS): |
Master's thesis/paper |
Study programme: |
1000471 |
Thesis comment: |
Univ. v Ljubljani, Fak. za računalništvo in informatiko |
Pages: |
75 str. |
ID: |
13748127 |