首页|一种基于异质信息网络的多维度语义融合推荐算法研究

一种基于异质信息网络的多维度语义融合推荐算法研究

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  • 万方数据
  • 维普
为解决目前互联网信息过载问题，推荐系统已经广泛应用于电子商务、新闻资讯和影视音乐网站等。推荐算法目标就是挖掘用户的潜在兴趣，为他们提供个性化的信息推送，最终解决信息过载的问题，从而为用户解决该分类问题，选择合适推荐算法就显得尤为重要，同时也是解决数据挖掘领域的重要方法。但当前推荐模型缺乏对多源头异质数据的有效利用，同时在聚合语义信息的过程中存在信息损失问题。为解决上述问题，提出了一种基于异质信息网络的多维度语义融合推荐算法模型。首先，通过元路径和异质图描述推荐任务内复杂的语义结构，然后，对于元路径所引导的邻域进行划分，并通过基于多层邻域交互捕获多尺度语义信息，最后，通过在低阶、高阶维度下引导多尺度语义信息融合。实验结果表明，该方法具有较高的准确度。
Research on a Multidimensional Semantic Fusion Recommendation Algorithm based on Heterogeneous Information Networks
To address the current issue of internet information overload,recommendation systems have been widely used in e-commerce,news and music websites,and other fields.The goal of rec-ommendation algorithms is to explore users'potential interests,provide personalized information push,and ultimately solve the problem of information overload.Therefore,it is particularly impor-tant to choose a suitable recommendation algorithm to solve the classification problem for users,and it is also an important method to solve the field of data mining.However,the current recommenda-tion model lacks effective utilization of heterogeneous data from multiple sources,and there is a problem of information loss in the process of aggregating semantic information.To address the above issues,this article proposes a multi-dimensional semantic fusion recommendation algorithm model based on heterogeneous information networks.Firstly,the complex semantic structure within the rec-ommendation task is described through meta paths and heterogeneous graphs.Then,the neighbor-hoods guided by the meta paths are divided,and multi-scale semantic information is captured through multi-layer neighborhood interaction.Finally,multi-scale semantic information fusion is guided in low and high order dimensions.The experimental results show that this method has high accuracy.

artificial intelligence technologyheterogeneous information networkmetapathseman-tic fusion

甘宏、王华武

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广州南方学院商学院, 510970,广州

江西新余国科科技股份有限公司,338034,江西,新余

人工智能技术 异质信息网络 元路径 语义融合

广东省教育厅质量工程项目2022年度广东省培育项目广东省普通高校特色新型智库项目广东省教育科学规划课题项目广东省重点建设学科科研能力提升项目广东省重点建设学科科研能力提升项目

2021GDJY02132022XK022021TSZK0082023GXJK6172022ZDJS1202021ZDJS129

2024

10.13990/j.issn1001-3679.2024.01.028

江西科学
江西省科学院

江西科学

影响因子：0.286
ISSN：1001-3679
年,卷(期)：2024.42(1)
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