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|Title:||On exploring semantic meanings of links for embedding social networks||Authors:||Xu, LC
|Issue Date:||2018||Publisher:||International World Wide Web Conferences Steering Committee Republic and Canton of Geneva, Switzerland �2018||Source:||Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018, Lyon, France, , Apr 23-27, 2018, p. 479-488 How to cite?||Abstract:||There are increasing interests in learning low-dimensional and dense node representations from the network structure which is usually high-dimensional and sparse. However, most existing methods fail to consider semantic meanings of links. Different links may have different semantic meanings because the similarities between two nodes can be different, e.g., two nodes share common neighbors and two nodes share similar interests which are demonstrated in node-generated content. In this paper, the former type of links are referred to as structure-close links while the latter type are referred to as content-close links. These two types of links naturally indicate there are two types of characteristics that nodes expose in a social network. Hence, we propose to learn two representations for each node, and render each representation responsible for encoding the corresponding type of node characteristics, which is achieved by jointly embedding the network structure and inferring the type of each link. In the experiments, the proposed method is demonstrated to be more effective than five recent methods on four social networks through applications including visualization, link prediction and multi-label classification.||URI:||http://hdl.handle.net/10397/80762||ISBN:||978-1-4503-5639-8||DOI:||10.1145/3178876.3186114||Rights:||This paper is published under the Creative Commons Attribution 4.0 International(CC BY 4.0) license. Authors reserve their rights to disseminate the work on theirpersonal and corporate Web sites with the appropriate attribution.
WWW 2018, April 23–27, 2018, Lyon, France
©2018 IW3C2 (International World Wide Web Conference Committee), publishedunder Creative Commons CC BY 4.0 License.
The following publication Xu, L. C., Wei, X. K., Cao, J. N., & Yu, P. S. (2018, April). On exploring semantic meanings of links for embedding social networks. In Proceedings of the 2018 World Wide Web Conference on World Wide Web (pp. 479-488). International World Wide Web Conferences Steering Committee is available at https://dx.doi.org/10.1145/3178876.3186114
|Appears in Collections:||Conference Paper|
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