Page 327 - 《软件学报》2025年第7期

3248 软件学报 2025 年第 36 卷第 7 期

态关系, 针对不同文本和标签之间的多样性关系进行更准确的建模, 从而有效地减少长尾标签的影响. 通过自适应
地调整标签之间的关联权重, FDGN 能够更好地适应复杂的多标签文本分类场景, 从而提高分类性能.

biogeography is the study of the geographical distribution of biological organisms the mindset of the engineer is that we can learn from nature
biogeography based optimization is a burgeoning nature inspired technique to find the optimal solution of the problem satellite image classification is
an important task because it is the only way we can know about the land cover map of inaccessible areas though satellite images have been classified
in past by using various techniques ,the researchers are always finding alternative strategies for satellite image classification so that they may be prepared
to select the most appropriate technique for the feature extraction task in hand this paper is focused on classification of the satellite image of a particular
land cover using the theory of biogeography based optimization the original bbo algorithm does not have the inbuilt property of clustering which is
required during image classification hence modifications have been proposed to the original algorithm and the modified algorithm is used to classify
the satellite image of a given region the results indicate that highly accurate land cover features can be extracted effectively when the proposed algorithm
is used
弱相关 强相关
图 3 标签 cs.CV 注意力权重可视化, 颜色深浅代表相关性程度

biogeography is the study of the geographical distribution of biological organisms the mindset of the engineer is that we can learn from nature
biogeography based optimization is a burgeoning nature inspired technique to find the optimal solution of the problem satellite image classification is
an important task because it is the only way we can know about the land cover map of inaccessible areas though satellite images have been classified
in past by using various techniques ,the researchers are always finding alternative strategies for satellite image classification so that they may be prepared
to select the most appropriate technique for the feature extraction task in hand this paper is focused on classification of the satellite image of a particular
land cover using the theory of biogeography based optimization the original bbo algorithm does not have the inbuilt property of clustering which is
required during image classification hence modifications have been proposed to the original algorithm and the modified algorithm is used to classify
the satellite image of a given region the results indicate that highly accurate land cover features can be extracted effectively when the proposed algorithm
is used
弱相关 强相关
图 4 标签 cs.LG 注意力权重可视化, 颜色深浅代表相关性程度

cs.SE 0.9
cs.SI 0.8
cs.CE
0.7
cs.LO
0.6
cs.CV
cs.LG 0.5
cs.SY 0.4
cs.IT
0.3
cs.DB
0.2
cs.CR
cs.SE cs.SI cs.CE cs.LO cs.CV cs.LG cs.SY cs.IT cs.DB cs.CR

图 5 数据库工程相关文本的动态图邻接矩阵

4 总 结

本文提出了一种基于特征融合动态图网络的多标签文本分类算法, 旨在克服现有方法对于标签关系图构建策
略的过度依赖以及对长尾标签的性能不足的问题. 算法通过动态图自适应地调整标签关系, 强调了重要关联并减
弱了无关信息, 同时结合了文本的全局和局部特征, 以更准确地预测标签关联. 通过基于动态图的图卷积网络生成
标签的最终表示, 为文本的多标签分类提供了有力支持. 实验结果验证了算法的有效性和可行性, 在多个数据集上
展现出了卓越的性能. 本研究为多标签文本分类领域的发展和实际应用提供了有益的参考和启发. 在未来的研究