Graph regularization methods for Web spam detection

Author:

Abernethy Jacob,Chapelle Olivier,Castillo Carlos

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference32 articles.

1. Becchetti, L., Castillo, C., Donato, D., Leonardi, S., & Baeza-Yates, R. (2006). Link-based characterization and detection of Web Spam. In Second international workshop on adversarial information retrieval on the Web (AIRWeb), Seattle, USA, August 2006.

2. Belkin, M., Matveeva, I., & Niyogi, P. (2004). Regularization and semi-supervised learning on large graphs. Lecture Notes in Computer Science, 3120, 624–638.

3. Belkin, M., Niyogi, P., & Sindhwani, V. (2005). On manifold regularization. In Proceedings of the tenth international workshop on artificial intelligence and statistics (AISTATS).

4. Benczúr, A., Csalogány, K., & Sarlós, T. (2006). Link-based similarity search to fight web spam. In Adversarial information retrieval on the Web (AIRWEB), Seattle, Washington, USA.

5. Blum, A., & Mitchell, T. (1998). Combining labeled and unlabeled data with co-training. In COLT: proceedings of the workshop on computational learning theory (pp. 92–100). San Mateo: Morgan Kaufmann.

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