Approximating web communities using subspace decomposition
| dc.contributor.author | Eustace, Justine | |
| dc.contributor.author | Wang, Xingyuan | |
| dc.contributor.author | Li, Junqiu | |
| dc.date.accessioned | 2021-05-05T09:57:28Z | |
| dc.date.available | 2021-05-05T09:57:28Z | |
| dc.date.issued | 2014 | |
| dc.description | Abstract. Full article available at https://doi.org/10.1016/j.knosys.2014.06.017 | en_US |
| dc.description.abstract | Herein, we propose an algorithm to approximate web communities from the topic related web pages. The approximation is achieved by subspace factorization of the topic related web pages. The factorization process reveals existing association between web pages such that the closely related web pages are extracted. We vary the approximation values to identify varied degrees of relationship between web pages. Experiments on real data sets show that the proposed algorithm reduces the impact of unrelated links and therefore can be used to control spam links in web pages. | en_US |
| dc.identifier.citation | Eustace, J., Wang, X., & Li, J. (2014). Approximating web communities using subspace decomposition. Knowledge-Based Systems, 70, 118-127. | en_US |
| dc.identifier.other | DOI: 10.1016/j.knosys.2014.06.017 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12661/2946 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Algorithm | en_US |
| dc.subject | Web pages | en_US |
| dc.subject | Web communities | en_US |
| dc.subject | Web graphs | en_US |
| dc.subject | Subspace decomposition | en_US |
| dc.subject | Information retrieval | en_US |
| dc.subject | Community detection | en_US |
| dc.subject | Spam detection | en_US |
| dc.title | Approximating web communities using subspace decomposition | en_US |
| dc.type | Article | en_US |