社交网络用户兴趣的数学建模

Zhenisgul Rakhmetullina, Roza Mukasheva, Raushan Mukhamedova, Bolat Batyrkhanov
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引用次数: 2

摘要

本文致力于研究对社交网络用户进行兴趣建模的现代方法,以及开发和实现我们自己的方法,该方法允许您以任何用户都可以理解的一组术语和类别的形式对兴趣进行建模。所开发的方法基于使用主题建模算法确定用户消息的主题,并考虑用户在社交图中的连接,对结果分布进行正则化。此外,还开发了一种方法,允许您自动将收到的主题与来自WikiPedia百科全书的一组概念和类别进行匹配。为了实现所开发的方法,建立了一个Twitter社交网络用户兴趣建模系统。文章描述了所实现系统的体系结构,并在测试数据集上对所构建的系统进行了实验测试,描述了所获得的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical Modeling of the Interests of Social Network Users
This article is devoted to the study of modern methods for modeling the interests social network users, as well as the development and implementation of our own method that allows you to model interests in the form of a set of terms and categories that are understandable to any user. The developed method is based on determining the topics of user messages using topic modeling algorithms and regularizing the resulting distribution, taking into account the user’s connections in the social graph. Also, a method was developed that allows you to automatically match the received topics with a set of concepts and categories from the WikiPedia encyclopedia. To implement the developed method, a system for modeling the interests of users of the Twitter social network has been built. The article describes the architecture of the implemented system, and also conducted experimental testing of the constructed system on a test dataset and describes the results obtained.
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