Consumption universes based supermarket layout through association rule mining and multidimensional scaling

Cil, Ibrahim

doi:10.1016/j.eswa.2012.01.192

Cited by 79 publications

(65 citation statements)

References 56 publications

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“…A pattern is interesting if it helps define a hypothesis, and an interesting pattern represents knowledge. This category of data mining is also used in such areas as business management (Cil, 2012), consumer profile analysis (Liao, Chen, & Deng, 2010), recommender systems (Lazcorreta, Botella, & Fernández-Caballero, 2008), (Adomavicius & Tuzhilin, 2005), adverse drug reactions (Ji et al, 2013) and genetics (Lin, Huang, & Leu, 2011).…”

Section: Association Rulesmentioning

confidence: 99%

Applying data mining techniques for spatial distribution analysis of plant species co-occurrences

Silva

Siqueira

Pinto

et al. 2016

Expert Systems with Applications

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The continuous growth of biodiversity databases has led to a search for techniques that can assist researchers. This paper presents a method for the analysis of occurrences of pairs and groups of species that aims to identify patterns in co-occurrences through the application of association rules of data mining. We propose, implement and evaluate a tool to help ecologists formulate and validate hypotheses regarding cooccurrence between two or more species. To validate our approach, we analyzed the occurrence of species with a dataset from the 50-ha Forest Dynamics Project on Barro Colorado Island (BCI). Three case studies were developed based on this tropical forest to evaluate patterns of positive and negative correlation. Our tool can be used to point co-occurrence in a multi-scale form and for multi-species, simultaneously, accelerating the identification process for the Spatial Point Pattern Analysis. This paper demonstrates that data mining, which has been used successfully in applications such as business and consumer profile analysis, can be a useful resource in ecology.

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Section: Association Rulesmentioning

confidence: 99%

Applying data mining techniques for spatial distribution analysis of plant species co-occurrences

Silva

Siqueira

Pinto

et al. 2016

Expert Systems with Applications

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show abstract

“…Chen and Lin [7] applied the multi-level association rule mining to explore the relationships between products as well as between product categories for resolving the product assortment and allocation problems in retailing. Cil [8] used buying association measure to create a category correlation matrix and applied the multidimensional scale technique to display the set of products in the store space. Although the association rules to assist managers in developing better layout for stores, their methods are more suitable for the case of new stores or joint sales.…”

Section: Introductionmentioning

confidence: 99%

Integrating Product Association Rules and Customer Moving Sequential Patterns for Product-to-Shelf Optimization

Tsai¹,

Huang²

2015

IJMLC

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Abstract-Previous studies in product-to-shelf assignment area usually applied the space elasticity to optimize product assortment and space allocation models. However, a well product-to-shelf assignment strategy should not only consider product assortment and space elasticity. Thus, this study develops a data mining method for solving the product-to-shelf assignment problem with consideration of both product association rules and moving behavior of consumer. Specifically, the first task of this research is to develop a method to discover product association rules and consumers' moving behaviors of which are collected through RFID systems in the store. The second task is to construct and solve a product-to-shelf assignment model, based on the information provided in the first task. In this research, products are classified as major item, minor item and the others. Only minor items are reassigned to ensure customers can follow their preferred moving behaviors. Experimental result shows our proposed method can reassign minor items to suitable shelves and increase cross-selling opportunity of major and minor items.Index Terms-Data mining, product-to-shelf assignment, moving and purchase patterns, customer behavior.

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“…In his research, he took customer receipt and product barcode information as data for the MigrosTürk supermarket, which has an important place in the retail sector, and analyzed it using the Apriori algorithm, according to the method of association rules. He then suggested a new store layout plan based on the resulting rules [15]. Hanguang and Yu worked on a Web based attack detection system with association rules mining and Apriori algorithm [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Determination of Association Rules with Market Basket Analysis: Application in the Retail Sector

Sagin

Ayvaz

2018

scjournal

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Consumption universes based supermarket layout through association rule mining and multidimensional scaling

Cited by 79 publications

References 56 publications

Applying data mining techniques for spatial distribution analysis of plant species co-occurrences

Applying data mining techniques for spatial distribution analysis of plant species co-occurrences

Integrating Product Association Rules and Customer Moving Sequential Patterns for Product-to-Shelf Optimization

Determination of Association Rules with Market Basket Analysis: Application in the Retail Sector

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