Personalization of Supermarket Product Recommendations

Lawrence, Richard D.; Almási, George; Kotlyar, Vladimir; Viveros, Marisa; Duri, Sastry S.

doi:10.1007/978-1-4615-1627-9_2

Cited by 90 publications

(82 citation statements)

References 9 publications

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“…In particular, the market basket analysis [1] can bring out the combinations of products that are susceptible of marketing strategies and may lead to better financial results. With market basket analysis [2], the administration of a super market can understand the behavior and purchasing habits of customers, through combinations of product market [3], which is repeated in large or small degree, as a habit. These combinations are called products association rules [4,5,6,7] and are the result of market basket analysis procedure.…”

Section: Market Basket Analysismentioning

confidence: 99%

Time Variations of Association Rules in Market Basket Analysis

Papavasileiou

Tsadiras

2011

IFIP Advances in Information and Communication Technology

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Abstract. This article introduces the concept of the variability of association rules of products through the estimate of a new indicator called overall variability of association rules (OCVR). The proposed indicator applied to super market chain products, tries to highlight product market baskets, with great variability in consumer behavior. Parameter of the variability of association rules in connection with changes in the purchasing habit during the course of time, can contribute further to the efficient market basket analysis and appropriate marketing strategies to promote sales. These strategies may include changing the location of the products on the shelf, the redefinition of the discount or even policy or even the successful of recommendation systems.

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Section: Market Basket Analysismentioning

confidence: 99%

Time Variations of Association Rules in Market Basket Analysis

Papavasileiou

Tsadiras

2011

IFIP Advances in Information and Communication Technology

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“…The SmartPad supermarket product recommender system [19] suggests new or previously unpurchased products to shoppers creating shopping lists on a personal digital assistant (PDA). The…”

Section: Hybrid Recommender Systemsmentioning

confidence: 99%

View through MetaLens: usage patterns for a meta-recommendation system

2004

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In a world where a person's number of choices can be overwhelming, recommender systems help users find and evaluate items of interest. They do so by connecting users with information regarding the content of recommended items or the opinions of other individuals. Such systems have become powerful tools in domains such as electronic commerce, digital libraries, and knowledge management.In this paper, we address such systems, as well as a relatively new class of recommender system called meta-recommenders. Meta-recommenders provide users with personalized control over the generation of a single recommendation list formed from a combination of rich data using multiple information sources and recommendation techniques. We discuss observations made from the public trial of a meta-recommender system in the domain of movies, and lessons learned from the incorporation of features that allow persistent personalization of the system. Finally, we consider the challenges of building real-world, usable meta-recommenders across a variety of domains.

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“…IBM has introduced pervasive computing in the context of retail [6,13,15] and the concept was further developed by project Albatros [20]. Our aim is to extend the reach of such information and communications environments in two ways: to include the consumer home through ambient intelligence devices and to provide a richer shopping experience within the supermarket space [1,9,16].…”

Section: Scenariosmentioning

confidence: 99%

A case study in pervasive retail

Roussos

Tuominen

Koukara

et al. 2002

Proceedings of the 2nd International Workshop on Mobile Commerce

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In this paper we discuss the rationale for the development of MyGrocer, a second-generation pervasive retail system, as well as its implications for the fast moving consumer goods (FMCG) sector. We will only touch upon the technology infrastructure and the required technical developments since these have been discussed extensively elsewhere. The focus here is on the one hand, on the analysis of the business forces that dictate the development of pervasive retail and on the other, the implications and the opportunities for innovative business models offered by the dis-intermediation effect of pervasive retail on the supply chain of FMCG. The MyGrocer system has undergone two phases of field-testing and is expected to be fully operational by the end of this year. The development of the MyGrocer architecture is a collaborative effort between industry and academia within Europe.

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Personalization of Supermarket Product Recommendations

Cited by 90 publications

References 9 publications

Time Variations of Association Rules in Market Basket Analysis

Time Variations of Association Rules in Market Basket Analysis

View through MetaLens: usage patterns for a meta-recommendation system

A case study in pervasive retail

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