The presence of near-replicas of documents is very common on the Web. Documents may be replicated completely or partially for different reasons (versions, mirrors, etc.), or the same resource can be associated to different URLs (dynamically generated pages, etc.). Whilst replication can improve information accessibility by the users, the presence of near-replicated documents can hinder the effectiveness of search engines (for example, decreasing the coverage). We propose a method to detect similar pages, in particular replicas and near-replicas, which is based on a pair of signatures. The first signature is obtained by a random projection of the bag-of-words vector representing the page contents. The second signature is computed by a recursive equation which exploits the connectivity among the Web pages to code the context of each page. The accuracy of the proposed approach is analyzed and validated by experimental results which show that on the given dataset near-replicas can be detected with a precision-recall of 93%.
DI IORIO, E., Diligenti, M., Gori, M., Maggini, M., Pucci, A. (2003). Detecting near-replicas on the Web by content and hyperlink analysis. In Proceedings of the IEEE/WIC International Conference on Web Intelligence (WIC 2003) (pp.249-255). Los Alamitos, USA : IEEE COMPUTER SOC [10.1109/WI.2003.1241201].
Detecting near-replicas on the Web by content and hyperlink analysis
DI IORIO, ERNESTO;DILIGENTI, MICHELANGELO;GORI, MARCO;MAGGINI, MARCO;PUCCI, AUGUSTO
2003-01-01
Abstract
The presence of near-replicas of documents is very common on the Web. Documents may be replicated completely or partially for different reasons (versions, mirrors, etc.), or the same resource can be associated to different URLs (dynamically generated pages, etc.). Whilst replication can improve information accessibility by the users, the presence of near-replicated documents can hinder the effectiveness of search engines (for example, decreasing the coverage). We propose a method to detect similar pages, in particular replicas and near-replicas, which is based on a pair of signatures. The first signature is obtained by a random projection of the bag-of-words vector representing the page contents. The second signature is computed by a recursive equation which exploits the connectivity among the Web pages to code the context of each page. The accuracy of the proposed approach is analyzed and validated by experimental results which show that on the given dataset near-replicas can be detected with a precision-recall of 93%.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/36822
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