Formal concept analysis: current trends and directions

Sarmah, Achyanta Kumar; Hazarika, Shyamanta M.; Sinha, Subrata

doi:10.1007/s10462-013-9404-0

Cited by 29 publications

(15 citation statements)

References 40 publications

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“…They point to the use of formal concept analysis as a possible tool to disaggregate data, allowing for more meaningful information. The result of their efforts, they claim, was to ‘… pinpoint [the] role and relevance of different attributes characterizing EU countries which are used to define the partial order.’ Sarmah et al () argue that learning is aided by formally presenting human thoughts. Sarmah et al .…”

Section: Methodsmentioning

confidence: 99%

“…Sarmah et al . () go on to note that FCA is one means of formalizing human thought, with such formalization being of assistance in considering the interrelationship between a context's intent and extent. Given the murkiness of many concepts in the sustainability arena, it is useful to have a tool such as FCA that can formalize thought and provide a framework for understanding the interrelationship between the possessor of an attribute (i.e., the object) and the attribute of the object.…”

Section: Methodsmentioning

confidence: 99%

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Using Formal Concept Analysis to Examine Water Disclosure in Corporate Social Responsibility Reports

Kleinman

Kuei

Lee

2017

Corp Soc Responsibility Env

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Corporate social responsibility (CSR) water disclosures vary in content, leading to concern about the quality and extent of such disclosures. This paper employs formal concept analysis (FCA) to examine water reporting of selected companies in the US food and beverage industry that have followed the water guidelines set forth by the Global Reporting Initiative (GRI) and in the disclosure guidelines of the CEO Water Mandate. Assessments of water consumption and water withdrawal were cited more often in our sample firms' CSR reports. FCA results also identify the major focus of our sample firms as setting sustainable water management goals and water quality strategy. Other important issues included leadership, partnership, and employee involvement. While the FCA text mining tool is demonstrated using water‐related behaviors here, it can be used to identify continuous improvement opportunities and examine many other issues of interest to corporate stakeholders in other industries and communities worldwide. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Using Formal Concept Analysis to Examine Water Disclosure in Corporate Social Responsibility Reports

Kleinman

Kuei

Lee

2017

Corp Soc Responsibility Env

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“…The Gödel represented t-norm is used accurately in the section of FLC based FCA where the semantics will partly covers by the fuzzy based DL which is most probably consent to synergies as in the crisp case of scenarios [24]. In Gödel based t-norm representations, sometimes it is holding the essential limit when the FLC based FCA implementation uses the weak-conjunction (WC) for the semantics of SoA while DL utilized the strong-conjunction (SC) for its concern semantics [25] [26]. The SC and WC correspond solitary for the Gödel based t-norm.…”

Section: Methodology Implicationsmentioning

confidence: 99%

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

Neelima

Sarma

2019

IJECE

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<span lang="EN-IN">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.</span>

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“…This fact can be realized by identifying states in navigation automata with formal concepts in concept lattices (such as these are understood in formal concept analysis [18]) 2 . The most extreme case, in which the number of states is 2 n -1 (with n the number of LOs), arises, for instance, by distinguishing each pair of metadata documents in a single element-value pair 3 .…”

Section: Reconfigurable Navigation Mapsmentioning

confidence: 99%

Learning object repositories with dynamically reconfigurable metadata schemata

Gayoso-Cabada

Rodríguez-Cerezo

Sierra

2016

2016 International Symposium on Computers in Education (SIIE)

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Abstract-In this paper we describe a model of learning object repository in which users have full control on the metadata schemata. Thus, they can define new schemata and they can reconfigure existing ones in a collaborative fashion. As consequence, the repository must react to changes in schemata in a dynamic and responsive way. Since schemata enable operations like navigation and search, dynamic reconfigurability requires clever indexing strategies, resilient to changes in these schemata. For this purpose, we have used conventional inverted indexing approaches and we have also devised a hierarchical clusteringbased indexing model. By using Clavy, a system for managing learning object repositories in the field of the Humanities, we provide some experimental results that show how the hierarchical clustering-based model can outperform the more conventional inverted indexes-based solutions.

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Formal concept analysis: current trends and directions

Cited by 29 publications

References 40 publications

Using Formal Concept Analysis to Examine Water Disclosure in Corporate Social Responsibility Reports

Using Formal Concept Analysis to Examine Water Disclosure in Corporate Social Responsibility Reports

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

Learning object repositories with dynamically reconfigurable metadata schemata

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