Exploring Attributes with Domain Knowledge in Formal Concept Analysis

Jonnalagadda, Annapurna; Cherukuri, Aswani Kumar

doi:10.2498/cit.1002114

Cited by 15 publications

(3 citation statements)

References 27 publications

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“…We must comment on the differences of our approach to the attribute exploration discussed in [15]. Attribute exploration is a manual interactive process for building the formal context and its concept lattice.…”

Section: A Combinatorial Testing Methodsmentioning

confidence: 99%

“…A concept lattice reduction method is proposed that successfully preserves minimum representation of the process data. An interactive process or building concept lattices called attribute exploration is discussed in [15]. Authors used existing domain experts' knowledge during the attribute exploration and demonstrated the process on two use-cases form healthcare domain.…”

Section: Related Researchmentioning

confidence: 99%

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Towards Automated Assessment Generation in e-Learning Systems Using Combinatorial Testing and Formal Concept Analysis

2021

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In this paper, we research the use of software combinatorial testing techniques and the Formal Concept Analysis method for preparing sets of questions for student assessment in e-learning systems. Utilizing these techniques and methods, we ensure that the selected questions optimally cover the course material and that each question combines multiple topics. Therefore, in this paper we introduce our method for preparing student assessments that performs automated combinatorial testing and selection of questions, as well as automated generation of appropriate sequences of questions. The input for our method is a set of questions labelled with attributes or features. This set of questions is pre-processed using the Formal Concept Analysis method, and then the combinatorial testing of question features is performed, which generates a concise list of test-cases covering all pairs or triples of question features. Correspondingly, our method helps in identifying and selecting a subset of questions that covers all generated test-cases. Afterwards, the Formal Concept Analysis method automatically generates suitable sequences of selected questions for formative student assessments in e-learning systems. In this paper we implemented the proposed combinatorial testing method, and also demonstrated the feasibility of the proposed method on a use-case from an actual e-learning system.

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Section: A Combinatorial Testing Methodsmentioning

confidence: 99%

Section: Related Researchmentioning

confidence: 99%

Towards Automated Assessment Generation in e-Learning Systems Using Combinatorial Testing and Formal Concept Analysis

2021

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“…FCA investigates the data which depicts relationship between the set of objects and the set of attributes. Various models based on FCA are introduced (Singh, Cherukuri & Li, 2017;Annapurna & Cherukuri, 2013;Cherukuri, Dias &Vieira, 2015;Cherukuri & Srinivas, 2010;Cherukuri, 2012;Shivhare & Cherukuri, 2016; in many areas according to the need. Cognitive functionalities Bidirectional Associative Memory has been modelled using FCA (Cherukuri, Ishwarya & Loo, 2015).…”

Section: Formal Concept Analysismentioning

confidence: 99%

A Pragmatic Approach to Understand Hebbian Cell Assembly

Cherukuri

Shivhare

Abraham

et al. 2021

International Journal of Cognitive Informatics and Natural Intelligence

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Formed at the cerebral cortex, neuron cell assemblies are regarded as basic units in cortical representation. Proposed by Hebb, these cell assemblies are regarded as the distributed neural representation of relevant objects, concepts or constellations. Each cell assembly contains a group of neurons having strong mutual excitatory connections. During a stimulus, these cells get activated. This activation either performs a given action or represent a given percept or concept in brain. This theory is in the strongest connection of the problem of concept forming in the brain. The challenge is to model coordinated activity among neurons in brain mathematically. The need of modelling it mathematically enables this paper to give clear view of functionality of Hebbian cell assembly. Therefore this paper proposes a pragmatic approach to Hebbian cell assemblies using mathematical model grounded in lattice based formalism that utilizes Galois connections. During this proposal, the authors also show the connections of the proposal to cognitive model of memory in particularly long-term memory (LTM).

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Modeling Associative Memories Using Formal Concept Analysis

Cherukuri

Ishwarya

Loo

2015

Advances in Intelligent Systems and Computing

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Abstract. Associative memory is one of the primary functions of the human brain. In the literature, there are several neural networks based models that represent associative memory with the help of pattern associations. In this paper, we model the associative memory activity using Formal Concept Analysis (FCA), which is a standard technique for data and knowledge processing. In our proposal, patterns are associated with the help of objectattribute relations and the memory is represented using the formal concepts generated using FCA. We show that the extent and intent relations in the concepts help us to recall the patterns bi-directionally. Further, we model the pattern recall process for the given input even when the exact match is not found in the memory, using the concept hierarchies in the concept lattice.

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Exploring Attributes with Domain Knowledge in Formal Concept Analysis

Cited by 15 publications

References 27 publications

Towards Automated Assessment Generation in e-Learning Systems Using Combinatorial Testing and Formal Concept Analysis

Towards Automated Assessment Generation in e-Learning Systems Using Combinatorial Testing and Formal Concept Analysis

A Pragmatic Approach to Understand Hebbian Cell Assembly

Modeling Associative Memories Using Formal Concept Analysis

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