Recommender system for surplus stock clearance

Title

Recommender system for surplus stock clearance

Creator

Agarwal V.; Vijayalakshmi A.

Description

Accumulation of the stock had been a major concern for retail shop owners. Surplus stock could be minimized if the system could continuously monitor the accumulated stock and recommend those which require clearance. Recommender Systems computes the data, shadowing the manual work and give efficient recommendations to overcome stock accumulation, creating space for new stock for sale to enhance the profit in business. An intelligent recommender system was built that could work with the data and help the shop owners to overcome the issue of surplus stock in a remarkable way. An item-item collaborative filtering technique with Pearson similarity metric was used to draw the similarity between the items and accordingly give recommendations. The results obtained on the dataset highlighted the top-N items using the Pearson similarity and the Cosine similarity. The items having the highest rank had the highest accumulation and required attention to be cleared. The comparison is drawn for the precision and recall obtained by the similarity metrics used. The evaluation of the existing work was done using precision and recall, where the precision obtained was remarkable, while the recall has the scope of increment but in turn, it would reduce the value of precision. Thus, there lies a scope of reducing the stock accumulation with the help of a recommender system and overcome losses to maximize profit. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved.

Source

International Journal of Electrical and Computer Engineering, Vol-9, No. 5, pp. 3813-3821.

Date

2019-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Inventory clearance; Recommender systems; Retail stock management; Stock accumulation; Stock clearance; Surplus stock

Coverage

Agarwal V., Department of Computer Science, CHRIST (Deemed to be University), India; Vijayalakshmi A., Department of Computer Science, CHRIST (Deemed to be University), India

Rights

All Open Access; Gold Open Access; Green Open Access

Relation

ISSN: 20888708

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijece.v9i5.pp3813-3821

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