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To address this issue, this paper introduces a negative sample debiased sampling contrastive learning (NDSCL), specifically tailored for node classification tasks. In particular, this method integrates contrastive learning with semi-supervised learning. A trained classifier assigns pseudo-labels to unlabeled data, and debiased sampling is applied to negative samples. Unlike other methods that focus on negative sample selection, NDSCL also addresses the imbalance in pseudo-label distribution by employing debiasing techniques. Finally, in conjunction with diffusion augmentation, the model is provided with diverse views as inputs to maximize the retention of underlying semantic information. Experimental results demonstrate that the proposed model significantly outperforms baseline models in node-level classification tasks across multiple network datasets. Moreover, the model not only enhances accuracy but also improves computational speed and memory requirements for handling large-scale graph data structures.<\/jats:p>","DOI":"10.1007\/s40747-024-01441-z","type":"journal-article","created":{"date-parts":[[2024,5,18]],"date-time":"2024-05-18T07:01:30Z","timestamp":1716015690000},"page":"5683-5701","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Node classification in complex networks based on multi-view debiased contrastive learning"],"prefix":"10.1007","volume":"10","author":[{"given":"Zhe","family":"Li","sequence":"first","affiliation":[]},{"given":"Lei","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Yandong","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Min","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Zhuanzheng","family":"Hang","sequence":"additional","affiliation":[]},{"given":"Bolun","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,18]]},"reference":[{"key":"1441_CR1","doi-asserted-by":"publisher","first-page":"102716","DOI":"10.1016\/j.jnca.2020.102716","volume":"166","author":"NN Daud","year":"2020","unstructured":"Daud NN, Ab Hamid SH, Saadoon M, Sahran F, Anuar NB (2020) Applications of link prediction in social networks: a review. 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