A social route recommender mechanism for store shopping support

Li, Yung-Ming; Lin, Lien-Fa; Ho, Chih‐Hsiang

doi:10.1016/j.dss.2016.11.004

Cited by 29 publications

(7 citation statements)

References 25 publications

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“…purchases, products accessed but not bought, time spent in the store, etc.) (Li et al, 2017). Moreover, they improve the service to the increasing consumers' involvement in the service co-creation (Blitz, 2016;Pan, 2016).…”

Section: Smart Retailingmentioning

confidence: 99%

To what extent luxury retailing can be smart?

Pantano

Passavanti

Priporas

et al. 2018

Journal of Retailing and Consumer Services

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Section: Smart Retailingmentioning

confidence: 99%

To what extent luxury retailing can be smart?

Pantano

Passavanti

Priporas

et al. 2018

Journal of Retailing and Consumer Services

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“…Hyperpersonalization is an advanced technique built over the concept of personalization, in which the model not only investigates the item or product that was bought, but also looks into other details such as location of purchase, mode of purchase, cost of purchase, keywords inserted during purchase, demographics of the person who purchased, etc. [34,124,130,135,139,203,204]. Hyperpersonalization delves into the intricate details and thereby produces much better and effective personalization, which has made it popular in recent times [5,29,146,205,206].…”

Section: Hyperpersonalization Filtering Techniquementioning

confidence: 99%

Fashion Recommendation Systems, Models and Methods: A Review

et al. 2021

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In recent years, the textile and fashion industries have witnessed an enormous amount of growth in fast fashion. On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information to users. Image-based fashion recommendation systems (FRSs) have attracted a huge amount of attention from fast fashion retailers as they provide a personalized shopping experience to consumers. With the technological advancements, this branch of artificial intelligence exhibits a tremendous amount of potential in image processing, parsing, classification, and segmentation. Despite its huge potential, the number of academic articles on this topic is limited. The available studies do not provide a rigorous review of fashion recommendation systems and the corresponding filtering techniques. To the best of the authors’ knowledge, this is the first scholarly article to review the state-of-the-art fashion recommendation systems and the corresponding filtering techniques. In addition, this review also explores various potential models that could be implemented to develop fashion recommendation systems in the future. This paper will help researchers, academics, and practitioners who are interested in machine learning, computer vision, and fashion retailing to understand the characteristics of the different fashion recommendation systems.

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“…There are basically three type of knowledge, knowledge about user, knowledge about items and knowledge about relation between user and item [15]. To achieve this, a popular approach which is ontology-based approach has been widely adopted in many research papers [11,12,16,17]. Ontologies are used to model the user profile, item data, and relationship between it.…”

Section: Knowledge-based Recommendation Techniquesmentioning

confidence: 99%

“…Recently, many researchers have enhanced the RS and apply in many domain such as e-commence [7,8], video [9], tourism [10], books [11] and social media [12]. The enhancements include optimizing the RS structure, algorithms and techniques.…”

Section: Introductionmentioning

confidence: 99%

Recommender System for Retail Domain

Chew

Haw

Subramaniam

2020

Proceedings of the 12th International Conference on Computer Modeling and Simulation

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Recommender system has been developed as a useful tool especially when we reached the era of big data and in the meanwhile the internet has been overwhelming with lots of choices. There is a need for people to filter the information to search for their needs and wants efficiently. E-commerce website such as Amazon and Netflix have been using recommender system to build and boost their sales through the personalization recommendation. With the success in the e-commerce area, researchers are keen on finding a method to boost traditional offline retailer sales thru the recommender system. Therefore, in this paper, we introduced the existing recommender system and discuss the method of filtering of each method. Then, we provide the overview of the recent paper in retailer and e-commerce domain to provide the insight and trends such as the filtering techniques and evaluation metric used. Several possible research direction has been discussed based on the current trends and problems. CCS Concepts• Information systems➝Information retrieval➝Retrieval tasks and goals➝Recommender systems.

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A social route recommender mechanism for store shopping support

Cited by 29 publications

References 25 publications

To what extent luxury retailing can be smart?

To what extent luxury retailing can be smart?

Fashion Recommendation Systems, Models and Methods: A Review

Recommender System for Retail Domain

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