Integrating Sustainability in the Fashion System Using Association Rules

Ciarapica, Filippo Emanuele; Sanctis, Ilaria De; Resta, Barbara; Dotti, Stefano; Gaiardelli, Paolo; Bandinelli, Romeo; Fani, Virginia; Rinaldi, Rinaldo

doi:10.1007/978-3-319-48511-9_20

Cited by 4 publications

(8 citation statements)

References 23 publications

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“…Table 5 shows some rules discovered by the algorithm. According to the results, the patterns {YarnElongationAt Break = (15.5-17.5]} and {YarnIrregularity = [7][8][9]} are the most frequent 1-itemsets, which indicates that they are the most influential parameters among the ones considered. Following these two parameters, the important attributes and their range values were determined as cf-items and mf-items and given as, for example, {YarnHairinessH = (3-4]} and {YarnCapillary = (3-4]} , respectively.…”

Section: Comparison Of Different Types Of Patternsmentioning

confidence: 98%

“…The aforementioned textile studies only used classification and clustering tasks of data mining for fabric data to get valuable information required for fabric quality. Although ARM has a very long history in many areas, especially in marketing, only a few studies [4][5][6][7] have been done so far in the textile industry. However, these studies do not aim to determine textile parameters; instead, they focus on different purposes such as textile marketing [4], ARM method verification by using a textile dataset [5,6], and environmental strategies developed by fashion companies [7].…”

Section: Related Workmentioning

confidence: 99%

“…Although ARM has a very long history in many areas, especially in marketing, only a few studies [4][5][6][7] have been done so far in the textile industry. However, these studies do not aim to determine textile parameters; instead, they focus on different purposes such as textile marketing [4], ARM method verification by using a textile dataset [5,6], and environmental strategies developed by fashion companies [7]. One of the studies in the literature [3] proposed a quality management system based on hybrid OLAP-association rule mining for extracting defect patterns in the garment industry.…”

Section: Related Workmentioning

confidence: 99%

“…FP-Growth is a scalable algorithm that discovers large volumes of frequent itemsets efficiently using an extended prefix-tree structure (FP-tree). While there are a number of classification and clustering studies in textile domain, ARM has only been used in several textile studies [3][4][5][6][7] so far. The present study is the first study where an ARM algorithm (FP-Growth) is implemented on a real-world textile dataset to discover relationships among yarn parameters and fabric properties.…”

Section: Introductionmentioning

confidence: 99%

“…5-17.5],(17.5-19.5],(19.5-21.5],(21.5-23.5] Yarn elongation at break (784.27[3][4][5][6][7][8][9], (9-27], (27-39], (39-462], (462-1419], (1419-2376] 18.75], (18.75-20.75], (20.75-23.125], (23.125-25..25 121.86 13.3 [100-111], (111-122], (122-133], (133-144] 1.75], (1.75-2.5], (2.5-3.25], (3.25-4] 1.75], (1.75-2.5], (2.5-3.25], (3.25-4] Yarn manufacturing method MVS, RAJ, SIRO, RING…”

mentioning

confidence: 99%

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Discovering the relationships between yarn and fabric properties using association rule mining

Yıldırım¹,

Birant²,

Alpyıldız³

2017

Turk J Elec Eng & Comp Sci

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Abstract:Investigation of the effects of yarn parameters on fabric quality and finding important parameters to achieve desired fabric properties are important issues for the design process with the aim to meet the needs of the textile industry and the consumer for complex and specific requirements of functionality. Despite many statistical and mathematical studies that predict and reveal specific properties of utilized yarn and fabric materials, a number of challenges continue to exist when evaluated in many perspectives, such as discovering complex relationships among material properties in data. Data mining plays an important role in discovering hidden patterns from fabric data and transforming it into knowledge. Therefore, the aim of the study is to uncover relationships between yarn parameters and fabric properties using an extended FP-Growth algorithm in association rule mining. This study extracts different types of frequent itemsets (closed, maximal, top-k, top-k closed, top-k maximal) that have not been determined in textile sector before.This article also proposes two novel concepts, closed frequent item and maximal frequent item, to identify significant items in data. In the experimental studies, the algorithm was executed on a real-world textile dataset with different support threshold values to compare the different types of patterns. Experimental results show that proposed approach is very useful for discovering rules related to yarn and fabric properties.

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Section: Comparison Of Different Types Of Patternsmentioning

confidence: 98%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Discovering the relationships between yarn and fabric properties using association rule mining

Yıldırım¹,

Birant²,

Alpyıldız³

2017

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

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Sustainable fashion: current and future research directions

Mukendi

Davies

Glozer

et al. 2020

EJM

168

101

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Purpose The sustainable fashion (SF) literature is fragmented across the management discipline, leaving the path to a SF future unclear. As of yet, there has not been an attempt to bring these insights together or to more generally explore the question of “what is known about SF in the management literature and where could the SF field go from there?”. The purpose of this paper is to bring together the field to identify opportunities for societal impact and further research. Design/methodology/approach A systematic literature review was conducted from the first appearances of SF in the management literature in 2000 up to papers published in June 2019, which resulted in 465 included papers. Findings The results illustrate that SF research is largely defined by two approaches, namely, pragmatic change and radical change. The findings reveal seven research streams that span across the discipline to explore how organisational and consumer habits can be shaped for the future. Research limitations/implications What is known about SF is constantly evolving, therefore, the paper aims to provide a representative sample of the state of SF in management literature to date. Practical implications This review provides decision makers with insights that have been synthesised from across the management field. Originality/value This review identifies knowledge gaps and informs managerial decision making in the field, particularly through serving as a foundation for further research.

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Effect of new generation Ftas onsustainable product innovation: empirical evidence fromvietnamese listed textile firms

Hồng Nga,

Dac Thanh,

Xuan Phuong

2023

ing. Solidar

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Introduction: The covid-19 pandemic has significantly changed consumption habits, with by cutting unnecessary spending on fashion products, and focusing on sustainable products. Therefore, greener textile innovation is currently a rapidly growing trend, bringing new sales and flexible production capabilities. The article presents impact of new generation FTA like EVFTA, CPTPP on sustainable textile product innovation. Problem: Greener production is dominant in several export industries. After the Covid-19 pandemic shifting from fast fashion to sustainable fashion is more and more changing. Objective: The aim of this study is to examine impact directly as well as indirectly the relationship between FTA expectation on SPIC via 2 mediating variable such as environmental regulation and CEO’s perception. Methodology: The study is exploratory research, it was modeled using PLS-SEM to test the relationships in the model. Results: Both Environment Regulation and CEO's perception play an important role as partial mediation in the relationship between FTA expectation and sustainable product innovation capability. Conclusion: This project seeks to generate a change in the behavior of the use towards efficiency and modification of user practices to favor the sustainability standard of the textile and garment firm. Originality: Through this research, integrated and sustainable textile and garment management strategies are formulated for green marketing strategies in Vietnam. Limitations: The lack of information provided by the municipality and access to the sampling points.

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Integrating Sustainability in the Fashion System Using Association Rules

Cited by 4 publications

References 23 publications

Discovering the relationships between yarn and fabric properties using association rule mining

Discovering the relationships between yarn and fabric properties using association rule mining

Sustainable fashion: current and future research directions

Effect of new generation Ftas onsustainable product innovation: empirical evidence fromvietnamese listed textile firms

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