ITR: Trust and the Information Consumer: A Graph Theory Approach

关于电子商务，尤其是在建立和评估单个网站的可信性方面，信任及其对消费者行为的影响的主题最近受到了越来越多的关注。然而，依赖互联网收集信息的消费者可以通过工具更好地服务于他们，这些工具可以集成来自许多不同来源的信息，并衡量集成的信息主体的可信度。我们建议开发一种方法来解决从多个来源组装信息产品并评估其可信度的问题。我们将利用文本分析、知识获取、图论和可视化以及统计推理等技术，使用户能够从一组网页生成自动摘要，评估其可信度，并直观地导航信息模型。最终的交付成果是实现该方法的软件包。这项拟议的研究将提供一种新技术，填补目前信息检索和信任评估技术留下的空白，从而使互联网社区受益。此外，我们建议开发的技术有可能对面临分析图值数据样本问题的广泛领域做出贡献。

The topic of trust and its influence on consumer behavior has received growing attention of late with respect to electronic commerce, especially with regard to establishing and evaluating the trustworthiness of a single web site. However, consumers who rely on the Internet for information gathering are better served by tools that integrate information from many different sources and measure the trustworthiness of the integrated body of information. We propose to develop a methodology that addresses this problem of assembling an information product from many sources and evaluating its trustworthiness. Drawing on techniques in text analysis, knowledge acquisition, graph theory and visualization, and statistical inference, we will enable the user to generate an automated summary from a group of web pages, evaluate its trustworthiness, and visually navigate the information models. The final deliverable is a software package that implements the methodology. The proposed research will benefit the Internet community by providing a new technology that fills the void left by current information retrieval and trust assessment technologies. In addition, the techniques we propose to develop have the potential to contribute to a wide variety of fields confronted with the problem of analyzing samples of graph-valued data.