Completing Description Logic Knowledge Bases using Formal Concept Analysis

We propose an approach for extending both the terminological and the assertional part of a Description Logic knowledge base by using information provided by the assertional part and by a domain expert. The use of techniques from Formal Concept Analysis ensures that, on the one hand, the interaction with the expert is kept to a minimum, and, on the other hand, we can show that the extended knowledge base is complete in a certain sense

Blended intelligence of FCA with FLC for knowledge representation from clustered data in medical analysis

Formal concept analysis is the process of data analysis mechanism with emergent attractiveness across various fields such as data mining, robotics, medical, big data and so on. FCA is helpful to generate the new learning ontology based techniques. In medical field, some growing kids are facing the problem of representing their knowledge from their gathered prior data which is in the form of unordered and insufficient clustered data which is not supporting them to take the right decision on right time for solving the uncertainty based questionnaires. In the approach of decision theory, many mathematical replicas such as probability-allocation, crisp set, and fuzzy based set theory were designed to deals with knowledge representation based difficulties along with their characteristic. This paper is proposing new ideological blended approach of FCA with FLC and described with major objectives: primarily the FCA analyzes the data based on relationships between the set of objects of prior-attributes and the set of attributes based prior-data, which the data is framed with data-units implicated composition which are formal statements of idea of human thinking with conversion of significant intelligible explanation. Suitable rules are generated to explore the relationship among the attributes and used the formal concept analysis from these suitable rules to explore better knowledge and most important factors affecting the decision making. Secondly how the FLC derive the fuzzification, rule-construction and defuzzification methods implicated for representing the accurate knowledge for uncertainty based questionnaires. Here the FCA is projected to expand the FCA based conception with help of the objective based item set notions considered as the target which is implicated with the expanded cardinalities along with its weights which is associated through the fuzzy based inference decision rules. This approach is more helpful for medical experts for knowing the range of patient’s memory deficiency also for people whose are facing knowledge explorer deficiency

Learning Description Logic Ontologies: Five Approaches. Where Do They Stand?

Abstract The quest for acquiring a formal representation of the knowledge of a domain of interest has attracted researchers with various backgrounds into a diverse field called ontology learning. We highlight classical machine learning and data mining approaches that have been proposed for (semi-)automating the creation of description logic (DL) ontologies. These are based on association rule mining, formal concept analysis, inductive logic programming, computational learning theory, and neural networks. We provide an overview of each approach and how it has been adapted for dealing with DL ontologies. Finally, we discuss the benefits and limitations of each of them for learning DL ontologies

Some Problems on Building Cognitive Robot

人类的智力与人类的涉身体验密不可分。因此，许多人工智能学者相信 在迈向更高级的人工智能的道路上，涉身人工智能是合理甚至是唯一的选择。 涉身人工智能与传统的人工智能的重要区别在于；强调了认知和意识的生 成不仅仅是一个“心智”（Mind）问题。同时，也与其所处环境(Environment)、 身体（Body）密切相关，三者同时在认知的形成过程中扮演着重要的角色； 强调“自我”在认知和意识中的重要作用，即以第一人称视角（First-person Perspective）来体验世界并形成相关的概念和知识，以“自我”为出发点运用这 些知识。 秉持这种思想，结合厦门大学智能科学系正在开...Human intelligence and our embodied experience are inseparable. Therefore, many scholars in AI community believe that the road to human-level intelligence, embodied artificial intelligence (EAI) is a reasonable or even the only option. There are two main differences between EAI and traditional AI methods: at first, EAI highlights that the formation of cognition and consciousness is more than ...学位：博士后院系专业：数学科学学院数学与应用数学系_人工智能基础学号：BHBG0005