Knowledge discovery and semantic learning in the framework of axiomatic fuzzy set theory

Liu, Xiaodong; Jia, Wenhao; Wang, Yuangang; Guo, Hongyue; Ren, Yan; Li, Zedong

doi:10.1002/widm.1268

Cited by 18 publications

(8 citation statements)

References 67 publications

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“…Our text granularity contains clear semantic information, and the coarse granularity is calculated by EI algebra to obtain a finer granularity with richer semantic information. EI algebra also has the following axioms (natural language axioms) [35] [36]:…”

Section: ) Ei Algebramentioning

confidence: 99%

A Text-Granulation Clustering Approach With Semantics for E-Commerce Intelligent Storage Allocation

2020

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With the hot rise and increasing popularity of e-commerce and online shopping, exponentially growing orders require to be picked up timely. In the order-based warehouse picking process, more intelligent optimization methods are urgently demanded to meet the maturity of robot technology. Due to the wide variety of SKUs (stock-keeping units) in warehouses, direct analysis based on orders can hardly get strong correlations among SKUs. Since orders and SKUs usually are presented in text form files, this paper proposes a clustering optimization algorithm based on text information granules which makes full use of context information and semantics. Storage assignment is determined by clustering SKUs first and then performing correlation analysis on the clustering results according to orders. The algorithm can give the semantic description of each cluster so that the clustering process is interpretable and transparent. Extensive experiments on a distribution center of a clothing production enterprise indicate 40.5 to 57.9% improvement in the average order picking distance compared with the ABC classification.

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Section: ) Ei Algebramentioning

confidence: 99%

A Text-Granulation Clustering Approach With Semantics for E-Commerce Intelligent Storage Allocation

2020

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“…According to Reference [21], ABS will get more attention in the field of BPM similarly to other areas like, e.g., social sciences. Following non-standard solutions, some authors use the axiomatic fuzzy set (AFS) theory to convert event logs into fuzzy sets, resulting in a powerful tool to model and store human knowledge and behavior [22]. In recent years, such an approach is more and more often applied in various disciplines-business intelligence, financial analysis, clinical tests, etc.…”

Section: Related Workmentioning

confidence: 99%

Process Discovery in Business Process Management Optimization

2019

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Appropriate business processes management (BPM) within an organization can help attain organizational goals. It is particularly important to effectively manage the lifecycle of these processes for organizational effectiveness in improving ever-growing performance and competitivity-building across the company. This paper presents a process discovery and how we can use it in a broader framework supporting self-organization in BPM. Process discovery is intrinsically associated with the process lifecycle. We have made a pre-evaluation of the usefulness of our facts using a generated log file. We also compared visualizations of the outcomes of our approach with different cases and showed performance characteristics of the cash loan sales process.

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“…Based on the Axiomatic Fuzzy Set (AFS) theory [18], this paper proposes a novel bi-clustering model for the identification of co-regulated genes. The AFS theory facilitates a way to transform data into fuzzy sets (membership functions) and implement their fuzzy logic operations, which provides a flexible and powerful tool for representing human knowledge and emulating the human recognition process.…”

Section: Brief Introduction Of a Fuzzy Bi-clustering Algorithm With A...mentioning

confidence: 99%

A Novel Fuzzy Bi-Clustering Algorithm with Axiomatic Fuzzy Set for Identification of Co-Regulated Genes

Xu,

Wang

2024

Mathematics

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The identification of co-regulated genes and their Transcription-Factor Binding Sites (TFBSs) are the key steps toward understanding transcription regulation. In addition to effective laboratory assays, various bi-clustering algorithms for the detection of the co-expressed genes have been developed. Bi-clustering methods are used to discover subgroups of genes with similar expression patterns under to-be-identified subsets of experimental conditions when applied to gene expression data. By building two fuzzy partition matrices of the gene expression data with the Axiomatic Fuzzy Set (AFS) theory, this paper proposes a novel fuzzy bi-clustering algorithm for the identification of co-regulated genes. Specifically, the gene expression data are transformed into two fuzzy partition matrices via the sub-preference relations theory of AFS at first. One of the matrices considers the genes as the universe and the conditions as the concept, and the other one considers the genes as the concept and the conditions as the universe. The identification of the co-regulated genes (bi-clusters) is carried out on the two partition matrices at the same time. Then, a novel fuzzy-based similarity criterion is defined based on the partition matrices, and a cyclic optimization algorithm is designed to discover the significant bi-clusters at the expression level. The above procedures guarantee that the generated bi-clusters have more significant expression values than those extracted by the traditional bi-clustering methods. Finally, the performance of the proposed method is evaluated with the performance of the three well-known bi-clustering algorithms on publicly available real microarray datasets. The experimental results are in agreement with the theoretical analysis and show that the proposed algorithm can effectively detect the co-regulated genes without any prior knowledge of the gene expression data.

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Knowledge discovery and semantic learning in the framework of axiomatic fuzzy set theory

Cited by 18 publications

References 67 publications

A Text-Granulation Clustering Approach With Semantics for E-Commerce Intelligent Storage Allocation

A Text-Granulation Clustering Approach With Semantics for E-Commerce Intelligent Storage Allocation

Process Discovery in Business Process Management Optimization

A Novel Fuzzy Bi-Clustering Algorithm with Axiomatic Fuzzy Set for Identification of Co-Regulated Genes

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