Semantic analysis and biological modelling in selected classes of cognitive information systems

Lidia Ogiela
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引用次数: 43

Abstract

Cognitive categorisation systems are used for in-depth analyses of data which contains significant layers of information. These layers consist of the semantic information found in the data sets, whose information allows the system executing data analysis processes to understand the data to a certain extent and to reason based on this analysed information. Such processes are executed by semantic data analysis systems which are called cognitive categorisation systems in the introduced classification of cognitive systems dedicated to analyses in various fields of application. Cognitive data analysis systems are also expanded by adding processes of learning new solutions hitherto unknown to the system because it had no appropriate pattern defined or because it had no data allowing the analysed data to be unambiguously assigned to its corresponding pattern. The ability to train the system so that it would correctly interpret the analysed data marks the beginning of the development of a new class of systems analysing data/individual features in the course of biological modelling, personalisation and personal identification processes. Identification systems are enhanced by adding elements of cognitive categorisation systems in order to execute an in-depth, more detailed personal analysis using the information collected in the system, whose information concerns not only the anatomical and physical features, but also, or maybe primarily, lesions found in various human organs. Such systems could be used in personal identification cases in which there are doubts and a risk arises due to reasoning from incomplete data sets. Adding semantic analysis modules to personal identification systems represents a novel scientific proposition which marks the beginning of the use of semantic analysis processes for biological modelling and personalisation tasks. The solutions proposed are illustrated with the example of selected E-UBIAS systems which analyse medical image data in combination with the identity analysis. The use of DNA cryptography and DNA code to analyse personal data makes it possible to unanimously assign analysed data to an individual at the personal identification stage. This publication presents also the system with semantic analysis processes conducted based on semantic interpretation and cognitive processes allows the possible lesions that the person suffers from to be identified and authorised.

认知信息系统的语义分析和生物建模
认知分类系统用于对包含重要信息层的数据进行深入分析。这些层由数据集中发现的语义信息组成,这些信息允许系统执行数据分析过程在一定程度上理解数据,并根据这些分析信息进行推理。这些过程由语义数据分析系统执行,在介绍的用于各种应用领域分析的认知系统分类中,这些系统被称为认知分类系统。认知数据分析系统还可以通过添加学习新解决方案的过程来扩展,因为系统没有适当的模式定义,或者因为它没有数据允许分析的数据明确地分配到相应的模式。训练系统使其正确解释分析数据的能力标志着在生物建模、个性化和个人识别过程中分析数据/个人特征的新一类系统发展的开始。通过添加认知分类系统的元素来增强识别系统,以便使用系统中收集的信息执行深入,更详细的个人分析,这些信息不仅涉及解剖和物理特征,而且可能主要涉及在各种人体器官中发现的病变。这种系统可用于由于不完整数据集的推理而产生怀疑和风险的个人身份识别案件。将语义分析模块添加到个人识别系统中代表了一个新的科学命题,它标志着在生物建模和个性化任务中使用语义分析过程的开始。本文以所选的E-UBIAS系统为例说明了所提出的解决方案,该系统结合身份分析对医学图像数据进行分析。使用DNA密码学和DNA代码来分析个人数据,可以在个人身份识别阶段一致地将分析的数据分配给个人。本出版物还介绍了基于语义解释和认知过程进行的语义分析过程的系统,允许识别和授权患者可能遭受的病变。
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来源期刊
Mathematical and Computer Modelling
Mathematical and Computer Modelling 数学-计算机:跨学科应用
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