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Title:Orodje za avtomatizacijo optimizacije SEO : magistrsko delo
Authors:ID Gračner, Gašper (Author)
ID Ojsteršek, Milan (Mentor) More about this mentor... New window
Files:.pdf MAG_Gracner_Gasper_2019.pdf (2,31 MB)
MD5: C4F9B42B8B9C502338D71A07BEC52BA4
PID: 20.500.12556/dkum/8f45624a-5f3e-4216-83f5-4244b61a2544
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:S tem magistrskim delom smo želeli predstaviti področje optimizacije spletnih strani ter opisati dejavnike, ki vplivajo na boljše iskalne rezultate. Avtorji del, povezanih z optimizacijo spletnih strani, največkrat poudarijo pomembnost ključnih besed. Naloga opisuje tradicionalne in moderne načine iskanja ključnih besed. Med moderne načine lahko prištevamo tudi avtomatizirano iskanje le-teh. Pristopi iskanja se med sabo močno razlikujejo, nekateri temeljijo na statističnih podatkih, drugi na oblikovnih lastnostih besedila, tretji pa na strojnem učenju. Predstavljen je po en algoritem iz posamezne kategorije ter primerjava uspešnosti s podatki, ki smo jih pridobili iz storitve DataForSEO.
Keywords:algoritmi iskanja ključnih besed, SEO-optimizacija, spletni iskalniki, obdelava naravnega jezika
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[G. Gračner]
Year of publishing:2019
Number of pages:VII, 75 f.
PID:20.500.12556/DKUM-75026 New window
UDC:004.659:81\'322.2(043.2)
COBISS.SI-ID:22796822 New window
NUK URN:URN:SI:UM:DK:L6NQBOHK
Publication date in DKUM:23.11.2019
Views:1799
Downloads:138
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:17.09.2019

Secondary language

Language:English
Title:SEO optimization tool
Abstract:This master thesis addresses area of search engine optimization. It describes all parts of web site important for better search results. A lot of search engine optimization related works point out importance of choosing right keywords. Thesis describes traditional and modern ways how to find a right keywords. Automatic keyword extraction belongs to modern and sophisticated approaches. Algorithms for automatic keyword extraction are split in three main groups. First group uses text statistical data, algorithms in second group are based on extracting text features and the third group is based on machine learning. Thesis describes one algorithm for each group and compares their efficiency based on results from DataForSEO service.
Keywords:keyword extraction algorithms, SEO-optimization, search engines, natural language processing


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