A Maximum Entropy Weighted Trust-Analysis Algorithm Based on Sources Clustering

HOU Sen; LUO Xing-guo; SONG Ke

doi:10.3969/j.issn.0372-2112.2015.05.024

您当前的位置：

首页 >

文章列表页 >

A Maximum Entropy Weighted Trust-Analysis Algorithm Based on Sources Clustering

更新时间：2025-07-16

- A Maximum Entropy Weighted Trust-Analysis Algorithm Based on Sources Clustering
- Acta Electronica Sinica Vol. 43, Issue 5, Pages: 993-999(2015)
- 作者机构：
  
  中国人民解放军信息工程大学信息技术研究所,河南,郑州,450002
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2015.05.024
  CLC： TP14
- Published：2015
- 稿件说明：
移动端阅览
HOU Sen, LUO Xing-guo, SONG Ke. A Maximum Entropy Weighted Trust-Analysis Algorithm Based on Sources Clustering[J]. Acta Electronica Sinica, 2015, 43(5): 993-999.
DOI：

HOU Sen, LUO Xing-guo, SONG Ke. A Maximum Entropy Weighted Trust-Analysis Algorithm Based on Sources Clustering[J]. Acta Electronica Sinica, 2015, 43(5): 993-999. DOI： 10.3969/j.issn.0372-2112.2015.05.024.

摘要

在信息网络中

不同的信息源以不同的可信性和准确性提供了各式各样的信息.为了预测这些信息反映事实的真实度

学者们提出了一些信任分析算法来迭代地计算信息源的信任度及其提供事实的准确度.然而这些算法往往忽略了信息源和事实描述对象之间的相关性.本文作者提出了一种基于信息源聚类的最大熵加权信任分析算法

该算法使我们能够在进行信任分析时有效地融合诸如描述对象属性、信息源关联性等信息.实验证明该算法能够明显的提高分析性能.

Abstract

In information network

different sources publish facts with different degrees of credibility and accuracy.To predict the truth values of the facts

several fact-finder algorithms are suggested which iteratively compute the trustworthiness of an information sourceand the accuracy of the facts it provides.However they ignore a great deal of relevant background and contextual information.In this paper

we proposed a novel maximum entropy weighted method to processing trust analysis

allowing us to elegantly incorporate knowledge such as the attributes of the objects and the implications of the sources.Experiments demonstrate that our algorithmsignificantly improves performance over existing.

关键词

Keywords

references

Views

1492

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Temporal-Pulse Amplitude Clustering-Based Unknown Radar Emitter Signal Sorting Method

Continuous Relation Extraction Technique Based on Dynamic Relational Prototypes

Pseudo-label Denoising and SAM Optimization for Large-scale Unsupervised Semantic Segmentation

Heuristic Clustering Algorithm Based on Sub-Game Perfect Equilibrium

Density Peaks Clustering Algorithm Based on Geodesic Distance and Cosine Mutual Reverse Nearest Neighbors for Manifold Datasets

Related Author

LIN Jin-jian

HUANG Ming-jun

SUN Hui-bo

LIN Zi-han

XIE Kai

ZHONG Jiang

DAI Qi-zhu

LI Xue

Related Institution

The 29th Research Institute of China Electronics Technology Group Corporation

Deptment of Electronics and Communication Engineering, Sun Yat-sen University of China

School of Electrical Engineering and Computer Science, The University of Queensland

School of Computer Science, Chongqing University

Key Laboratory of Dependable Service Computing in Cyber Physical Society, Chongqing University

⁰