用Vague极限、Vague余极限和Vague交换性描述的数据上的模式
Patterns on data described by vague limits, vague colimits and vague commutativity
摘要：
特别是机器学习和一般人工智能的发展受到缺乏适当框架来指定和集成学习过程、数据转换过程和数据模型的强烈制约。在这项工作中，我们将传统的代数规范方法扩展到这种类型的框架。图的极限和共极限是不同数学领域的基本概念，在语义建模中具有重要意义。我们的工作的目的是研究扩展这些代数框架的规范的模糊结构和数据的模糊模式的描述的可能性。
英文摘要：
The development of machine learning in particular and artificial intelligent in general has been strongly conditioned by the lack of an appropriated framework to specify and integrate learning processes, data transformation processes and data models. In this work we extend traditional algebraic specification methods to this type of framework. Limits and colimits of diagrams are universal constructions fundamental in different mathematical domains importance in semantic modeling. The aim of our work is to study the possibility of extending these algebraic frameworks to the specification of vague structures and to the description of vague patterns on data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
