A reference collection for web spam

Author:

Castillo Carlos1,Donato Debora1,Becchetti Luca2,Boldi Paolo3,Leonardi Stefano2,Santini Massimo3,Vigna Sebastiano3

Affiliation:

1. Università di Roma, Rome, Italy and Yahoo! Research, Barcelona, Catalunya, Spain

2. Università di Roma, Rome, Italy

3. Università degli Studi, Milan, Italy

Abstract

We describe the WEBSPAM-UK2006 collection, a large set of Web pages that have been manually annotated with labels indicating if the hosts are include Web spam aspects or not. This is the first publicly available Web spam collection that includes page contents and links, and that has been labelled by a large and diverse set of judges.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Management Information Systems

Reference17 articles.

1. Detecting nepotistic links by language model disagreement

2. {Benczúr et al. 2006b} Benczúr A. A. Csalogány K. and Sarlós T. (2006b). Link-based similarity search to fight web spam. In Adversarial Information Retrieval on the Web (AIRWEB) Seattle Washington USA. {Benczúr et al. 2006b} Benczúr A. A. Csalogány K. and Sarlós T. (2006b). Link-based similarity search to fight web spam. In Adversarial Information Retrieval on the Web (AIRWEB) Seattle Washington USA.

3. UbiCrawler: a scalable fully distributed Web crawler

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