Text classification in Turkish marketing domain and context-sensitive ad distribution

Engin, Melih
Online advertising has a continuously increasing popularity. Target audience of this new advertising method is huge. Additionally, there is another rapidly growing and crowded group related to internet advertising that consists of web publishers. Contextual advertising systems make it easier for publishers to present online ads on their web sites, since these online marketing systems automatically divert ads to web sites with related contents. Web publishers join ad networks and gain revenue by enabling ads to be displayed on their sites. Therefore, the accuracy of automated ad systems in determining ad-context relevance is crucial. In this thesis we construct a method for semantic classification of web site contexts in Turkish language and develop an ad serving system to display context related ads on web documents. The classification method uses both semantic and statistical techniques. The method is supervised, and therefore, needs processed sample data for learning classification rules. Therefore, we generate a Turkish marketing dataset and use it in our classification approaches. We form successful classification methods using different feature spaces and support vector machine configurations. Our results present a good comparison between these methods.


Coherent Personalized Paragraph Generation for a Successful Landing Page
Çetinkaya, Yusuf Mucahit; Toroslu, İsmail Hakkı; Davulcu, Hasan (2022-11-12)
Social media has become an important place for online marketing like never before. Businesses use various techniques to identify and reach potential customers across multiple platforms and deliver a message to grab their attention. A notable post could attract potential customers to the product landing page. However, the acquisition is only the beginning. The landing page should respond to the visitor's need for persuasion to increase conversion rates. Showing every visitor the same page is far from that go...
Analyzing and Mining Comments and Comment Ratings on the Social Web
SİERSDORFER, Stefan; CHELARU, Sergiu; Pedro, Jose San; Altıngövde, İsmail Sengör; NEJDL, Wolfgang (Association for Computing Machinery (ACM), 2014-06-01)
An analysis of the social video sharing platform YouTube and the news aggregator Yahoo! News reveals the presence of vast amounts of community feedback through comments for published videos and news stories, as well as through metaratings for these comments. This article presents an in-depth study of commenting and comment rating behavior on a sample of more than 10 million user comments on YouTube and Yahoo! News. In this study, comment ratings are considered first-class citizens. Their dependencies with t...
How useful is social feedback for learning to rank YouTube videos?
CHELARU, Sergiu; Orellana-Rodriguez, Claudia; Altıngövde, İsmail Sengör (Springer Science and Business Media LLC, 2014-09-01)
A vast amount of social feedback expressed via ratings (i.e., likes and dislikes) and comments is available for the multimedia content shared through Web 2.0 platforms. However, the potential of such social features associated with shared content still remains unexplored in the context of information retrieval. In this paper, we first study the social features that are associated with the top-ranked videos retrieved from the YouTube video sharing site for the real user queries. Our analysis considers both r...
A tool for network simulation of massively multiplayer online games
Bozcan, Selçuk; İşler, Veysi; Department of Computer Engineering (2008)
Massively multiplayer online games (MMOGs) have become highly popular in the last decade and now attract millions of users from all over the world to play in an evolving virtual world concurrently over the Internet. The high popularity of MMOGs created a rapidly growing market and this highly dynamic market has forced the game developers to step up competitively. However, MMOG development is a challenging and expensive process. In this study, we have developed a network simulation tool which can be used to ...
Finding Online Health-Related Information: Usability Issues Of Health Portals
Gürel Köybaşı, Nergis Ayşe; Çağıltay, Kürşat (2012-08-29)
As Internet and computers become widespread, health portals offering online health-related information become more popular. The most important point for health portals is presenting reliable and valid information. Besides, portal needs to be usable to be able to serve information to users effectively. This study aims to determine usability issues emerging when health-related information is searched on a health portal. User-based usability tests are conducted and eye movement analyses are used in addition to...
Citation Formats
M. Engin, “Text classification in Turkish marketing domain and context-sensitive ad distribution,” M.S. - Master of Science, Middle East Technical University, 2009.