Text Classification in the Turkish Marketing Domain for Context Sensitive Ad Distribution

Date

2009-09-16

Author

Engin, Melih
Can, Tolga

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper, we construct and compare several feature extraction approaches in order to find a better solution for classification of Turkish web documents in the marketing domain. We produce our feature extraction techniques using characteristics of the Turkish language, structures of web documents and online content in the marketing domain. We form datasets in different feature spaces and we apply several Support Vector Machine (SVM) configurations on these datasets. We conduct our study considering the performance needs of practical context sensitive systems. Our results show that linear kernel classifiers achieve the best performance in terms of accuracy and speed on text documents expressed as keyword root features.

Subject Keywords

Text classification, Data mining, Machine learning, Artificial intelligence, Information retrieval, World wide web

URI

https://hdl.handle.net/11511/43098

DOI

https://doi.org/10.1109/iscis.2009.5291861

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

M. Engin and T. Can, “Text Classification in the Turkish Marketing Domain for Context Sensitive Ad Distribution,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43098.