基于相似度的电子邮件挖掘代理

V. Loia, S. Senatore, M. Sessa
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引用次数: 3

摘要

近年来,随着互联网的不断普及,再加上向许多人发送电子邮件变得非常简单,人们花在处理不必要和不相关的电子邮件上的时间越来越多。总的来说,我们注意到科学界和工业界的努力一直集中在智能过滤服务的想法上。我们的方法是不同的:用户希望将电子邮件发送给合适的读者,即其“配置文件”与电子邮件本身的内容兼容的用户。通过基于相似性的网络,根据与电子邮件争论相关的主题来描述配置文件。电子邮件作者利用基于相似性的推理,在客户端建立了这种认知框架。然后,一个基于移动计算的搜索引擎被触发:许多自主代理被创建并发送到网络上。代理像网络爬行蜘蛛一样工作,不是不加选择地探索网络,而是直接在潜在的读者主机上搜索与领域相关的文档。智能体从这类文档中提取基于逻辑的知识,并通过相似度推理引擎进行处理。结果,代理返回用户对接收潜在电子邮件的兴趣程度的评估。在客户端,收集器接收不同的评估,以便通过灵活的机制定义最终的用户邮件列表。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Similarity-based agents for e-mail mining
With Internet use continuing to explode, and due to the simplicity of sending e-mails to many people, recent years have seen the time spent in dealing with unnecessary and irrelevant e-mails increasing. In general, we note that the efforts of the scientific and industrial communities have been focused on the idea of smart filtering services. Our approach is different: the user wishes to send an e-mail to an appropriate reader, i.e. a user whose "profile" is compatible with the content of the e-mail itself. The profile is described in terms of topics that are related to the e-mail argument through a similarity-based network. The e-mail writer establishes this cognitive frame on the client-side, exploiting similarity-based reasoning. Then a search engine, based on mobile computation, is triggered: a number of autonomous agents are created and sent on to the network. The agents work as a Web-crawling spider, not exploring the net indiscriminately but searching domain-relevant documents directly on potential reader hosts. From this kind of document, the agent extracts logic-based knowledge that is processed by the similarity deduction engine. As a result, the agent returns an evaluation of the users' degree of interest in receiving the potential e-mail. On the client-side, a collector receives the different evaluations in order to define the final user mailing list by means of a flexible mechanism.
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