摘要翻译:
在我们的理解中,思维导图是一个自适应引擎,基本上是在现有事务流的基础上增量工作的。通常,思维导图由符号细胞组成,这些符号细胞相互连接,并根据事务流而变得更强或更弱。根据潜在的生物学原理,这些象征性细胞及其连接也可以适应地生存或死亡,形成不同大小的细胞团。在本研究中,我们试图证明思维导图在不同的应用场景下的适用性,例如作为一个底层管理系统来表示计算机网络中正常和异常的流量行为,支持搜索引擎中的用户行为检测,或者作为一个隐藏的自然语言交互的通信层。
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英文标题:
《Symbolic Computing with Incremental Mindmaps to Manage and Mine Data
Streams - Some Applications》
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作者:
Claudine Brucks, Michael Hilker, Christoph Schommer, Cynthia Wagner,
Ralph Weires
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最新提交年份:
2009
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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:
In our understanding, a mind-map is an adaptive engine that basically works incrementally on the fundament of existing transactional streams. Generally, mind-maps consist of symbolic cells that are connected with each other and that become either stronger or weaker depending on the transactional stream. Based on the underlying biologic principle, these symbolic cells and their connections as well may adaptively survive or die, forming different cell agglomerates of arbitrary size. In this work, we intend to prove mind-maps' eligibility following diverse application scenarios, for example being an underlying management system to represent normal and abnormal traffic behaviour in computer networks, supporting the detection of the user behaviour within search engines, or being a hidden communication layer for natural language interaction.
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PDF链接:
https://arxiv.org/pdf/0902.3196


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