- Tytuł:
- Antyscam : Practical Web Spam Classifier
- Autorzy:
-
Luckner, Marcin
Gad, Michał
Sobkowiak, Paweł - Powiązania:
- https://bibliotekanauki.pl/articles/226008.pdf
- Data publikacji:
- 2019
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
web spam detection
spam detection
imbalanced sets classification
automatic classification
machine learning - Opis:
- To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting–up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period.
- Źródło:
-
International Journal of Electronics and Telecommunications; 2019, 65, 4; 713-722
2300-1933 - Pojawia się w:
- International Journal of Electronics and Telecommunications
- Dostawca treści:
- Biblioteka Nauki
Artykuł