Automatic Indexing and Information Visualization: A Study Based on Paraconsistent Logics

Carlos Alberto Corrêa, Nair Yumiko Kobashi
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Abstract

This paper reports a research to evaluate the potential and the effects of use of annotated Paraconsistent logic in automatic indexing. This logic attempts to deal with contradictions, concerned with studying and developing inconsistency-tolerant systems of logic. This logic, being flexible and containing logical states that go beyond the dichotomies yes and no, permits to advance the hypothesis that the results of indexing could be better than those obtained by traditional methods. Interactions between different disciplines, as information retrieval, automatic indexing, information visualization, and nonclassical logics were considered in this research. From the methodological point of view, an algorithm for treatment of uncertainty and imprecision, developed under the Paraconsistent logic, was used to modify the values of the weights assigned to indexing terms of the text collections. The tests were performed on an information visualization system named Projection Explorer (PEx), created at Institute of Mathematics and Computer Science (ICMC – USP São Carlos), with available source code. PEx uses traditional vector space model to represent documents of a collection. The results were evaluated by criteria built in the information visualization system itself, and demonstrated measurable gains in the quality of the displays, confirming the hypothesis that the use of the para-analyser under the conditions of the experiment has the ability to generate more effective clusters of similar documents. This is a point that draws attention, since the constitution of more significant clusters can be used to enhance information indexing and retrieval. It can be argued that the adoption of non-dichotomous (non-exclusive) parameters provides new possibilities to relate similar information.
自动索引与信息可视化:基于副一致逻辑的研究
本文报道了一项研究,评估了在自动标引中使用带注释的副一致逻辑的潜力和效果。这种逻辑试图处理矛盾,涉及研究和发展逻辑的不一致容忍系统。这种逻辑是灵活的,并且包含超越“是”和“否”二分类的逻辑状态,允许提出这样的假设,即索引的结果可能比传统方法获得的结果更好。该研究考虑了信息检索、自动标引、信息可视化和非经典逻辑等不同学科之间的相互作用。从方法学的角度来看,在副一致逻辑下开发的一种处理不确定性和不精确性的算法用于修改分配给文本集合索引项的权重值。测试是在数学和计算机科学研究所(ICMC - USP ss o Carlos)创建的一个名为投影资源管理器(Projection Explorer, PEx)的信息可视化系统上进行的,并提供了源代码。PEx使用传统的向量空间模型来表示集合的文档。结果通过信息可视化系统本身建立的标准进行评估,并证明了显示质量的可测量增益,证实了在实验条件下使用辅助分析器能够生成更有效的类似文档簇的假设。这是值得注意的一点,因为更重要的聚类的构成可以用来增强信息索引和检索。可以认为,采用非二分类(非排他性)参数为关联类似信息提供了新的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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