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摘要翻译：
人工免疫系统已经成功地用于建立电影数据库的推荐系统。在本研究中，尝试将这一思想推广到web站点推荐中。一个超过1000个人的web配置文件（或者称为首选项/喜爱/书签文件）的集合将被使用。URL将使用Open Directory Project的DMOZ（Directory Mozilla）数据库作为我们的本体进行分类。这将被用作人工免疫系统的数据，而不是实际地址。第一次尝试将涉及使用一个简单的分类代码号与该分类代码内的页数耦合。但是，该实现没有利用DMOZ的层次树状结构。然后将考虑为web配置文件构造一个相似性度量，该度量利用这种分层信息来建立一个更好的信息人工免疫系统。
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英文标题：
《An Artificial Immune System as a Recommender System for Web Sites》
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作者：
Tom Morrison and Uwe Aickelin
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最新提交年份：
2008
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Neural and Evolutionary Computing 神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of the Open Directory Project as our ontology. This will then be used as the data for the Artificial Immune Systems rather than the actual addresses. The first attempt will involve using a simple classification code number coupled with the number of pages within that classification code. However, this implementation does not make use of the hierarchical tree-like structure of DMOZ. Consideration will then be given to the construction of a similarity measure for web profiles that makes use of this hierarchical information to build a better-informed Artificial Immune System.
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PDF链接：
https://arxiv.org/pdf/0804.0573
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