Geografska segmentacija uporabnikov za uporabo v oglaševanju

diplomsko delo

Blaž Dolenc (Author), Blaž Zupan (Mentor)

Abstract

V današnjem spletnem oglaševanju ni več edini cilj prikazati oglasa čim večjemu številu potencialnih kupcev, temveč si oglaševalci vse bolj prizadevajo oglas prikazati tistemu, ki ga bo najverjetneje zanimal. Na primer, če poznamo uporabnikovo okvirno lokacijo, lahko na podlagi prejšnjih obiskovalcev napovemo klik oglasa. Potrebo po geografski segmentaciji uporabnikov so zaznali tudi pri podjetju Zemanta, kjer so študentom zastavili izziv, pri katerem je bilo potrebno obiskovalce spletnih strani razdeliti glede na poštno številko iz katere prihajajo, ter to uporabiti kot podlago za napoved klika. Cilj naloge je bilo poiskati čim bolj smiselne skupine uporabnikov, ter jih ustrezno predstaviti, v drugem delu pa zgraditi napovedni model za napovedovanje klika na oglas, ki bo dosegal točnost napovedi AUC okoli 0,75. V nalogi poročamo o naši rešitvi tega problema, ki uporablja vrsto tehnik s področja strojnega učenja. Končna razdelitev uporabnikov, ki jo predlagamo, je obsegala 20 skupin, ki so se med seboj močno razlikovale glede na gostoto poselitve, urbanizacije in ostalih demografskih dejavnikov. Prikaz skupin na zemljevidu je pokazal, da je razdelitev smiselna. Končni AUC na testnih podatkih je znašal 0,79.

Keywords

iskanje skupin v podatkih;gručenje;strojno učenje;računalništvo;računalništvo in informatika;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2015
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[B. Dolenc]
UDC:	004.85:659.11(043.2)
COBISS:	1536527811
Views:	808
Downloads:	118
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Geographic segmentation of users and its use in advertising
Secondary abstract:	In modern web advertising the goal is not only deliver an ad to a broad number of customers, but to target particular customers who are more likely to be interested in content. If the user location is known, we can estimate click on ad based on previous visitors. The company Zemanta recognized the need for geographic audience segmentation, and they have invited students to solve their challenge. The goal was geographic segmentation of web pages visitors based on the ZIP code they come from and development of a prediction model, which can estimate the probability of click on the ad, with accuracy (AUC score) around 0,75. In this dissertation, we describe our the solution to the challenge. Our user segmentation identified 20 groups. There were large differences between them considering population density, urbanization and other demographic indicators. Plotting results on map revealed, that segmentation is meaningful. Our final AUC score on test data was 0,79.
Secondary keywords:	clustering;data mining;machine learning;computer science;computer and information science;diploma;
File type:	application/pdf
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:	42 str.
ID:	8966323