Biomimetic design through natural language analysis to facilitate cross-domain information retrieval
Biomimetic design through natural language analysis to facilitate cross-domain information retrieval
复制标题
DOI：
10.1017/s0890060407070138
复制
发表时间：
2007-12-01
影响因子：
2.1
通讯作者：
Shu, L. H.
中科院分区：
文献类型：
--
作者：
Chiu, Ivey;Shu, L. H.
仿生学或生物启发设计使用类似的生物现象来开发工程问题的解决方案。仿生设计的几个例子来自个人对生物现象的观察。然而，许多工程师的生物学知识可能是有限的，从而降低了生物启发解决方案的潜力。我们的仿生设计方法利用了大量的生物学知识已经在书籍，期刊等，通过对这些现有的自然语言资源进行关键字搜索。由于自然语言的模糊性和不精确性，自然语言处理遇到了固有的挑战。检索相关跨域信息的一个挑战涉及域词汇表或词典的差异。一个对生物学家有意义的关键词，工程师可能不会想到。对于一个涉及清洁（即清除污垢）的示例问题，一位生物化学家建议使用关键字“defend”。对于大多数工程师来说，Defend并不是一个明显的关键字，defend和“clean/remove”在词汇引用中也没有直接的关系。然而，以前的工作表明，生物现象检索的关键字捍卫提供了有用的刺激，并产生了成功的概念，清洁/删除的问题。在本文中，我们描述了一种使用自然语言分析系统地桥接不同生物学和工程领域的方法。对于clean/remove示例，我们能够通过算法生成几个具有生物学意义的关键字，包括defend，这些关键字与工程问题没有明显关系。我们开发了一种方法来组织和排名的一组生物学意义的关键字确定，并证实，我们可以实现类似的结果，在封装和微组装的其他两个例子。虽然我们专门解决从生物学跨域信息检索，本文中提出的桥接过程并不限于生物学，并可以用于任何其他领域的适当的特定领域的知识来源和参考文献的可用性。
Biomimetic, or biologically inspired, design uses analogous biological phenomena to develop solutions for engineering problems. Several instances of biomimetic design result from personal observations of biological phenomena. However, many engineers' knowledge of biology may be limited, thus reducing the potential of biologically inspired solutions. Our approach to biomimetic design takes advantage of the large amount of biological knowledge already available in books, journals, and so forth, by performing keyword searches on these existing natural-language sources. Because of the ambiguity and imprecision of natural language, challenges inherent to natural language processing were encountered. One challenge of retrieving relevant cross-domain information involves differences in domain vocabularies, or lexicons. A keyword meaningful to biologists may not occur to engineers. For an example problem that involved cleaning, that is, removing dirt, a biochemist suggested the keyword "defend." Defend is not an obvious keyword to most engineers for this problem, nor are the words defend and "clean/remove" directly related within lexical references. However, previous work showed that biological phenomena retrieved by the keyword defend provided useful stimuli and produced successful concepts for the clean/remove problem. In this paper, we describe a method to systematically bridge the disparate biology and engineering domains using natural language analysis. For the clean/remove example, we were able to algorithmically generate several biologically meaningful keywords, including defend, that are not obviously related to the engineering problem. We developed a method to organize and rank the set of biologically meaningful keywords identified, and confirmed that we could achieve similar results for two other examples in encapsulation and microassembly. Although we specifically address cross-domain information retrieval from biology, the bridging process presented in this paper is not limited to biology, and can be used for any other domain given the availability of appropriate domain-specific knowledge sources and references.