Please use this identifier to cite or link to this item:
Title: An Experimental Study on Predictive Models Using Hierarchical Time Series
Authors: Silva,AM
Rita Paula Ribeiro
João Gama
Issue Date: 2015
Abstract: Planning strategies play an important role in companies' management. In the decision-making process, one of the main important goals is sales forecasting. They are important for stocks planing, shop space maintenance, promotions, etc. Sales forecasting use historical data to make reliable projections for the future. In the retail sector, data has a hierarchical structure. Products are organized in hierarchical groups that reflect the business structure. In this work we present a case study, using real data, from a Portuguese leader retail company. We experimentally evaluate standard approaches for sales forecasting and compare against models that explore the hierarchical structure of the products. Moreover, we evaluate different methods to combine predictions for the different hierarchical levels. The results show that exploiting the hierarchical structure present in the data systematically reduces the error of the forecasts.
metadata.dc.type: conferenceObject
Appears in Collections:LIAAD - Articles in International Conferences

Files in This Item:
File Description SizeFormat 
  Restricted Access
733.78 kBAdobe PDFView/Open Request a copy

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.