Real Time Shop-Type Recommendation System

This book deals with Real Time shop-type recommendation system, to generate the appropriate Real Time shop-type recommendations based on popularity prediction a feature fusion matrix factorization method is suggested. When an investor/shop owner decides to open a new shop on his available place and if there are various shops of different types, then Real Time shop-type recommendation can be done in following way: The location features fs and the commercial features Cst of each candidate type are required to be captured first. The set of feature values extracted for selected type t are given as a input to the feature fusion matrix factorization model. The popularity value for each type is calculated by using extracted feature values and value obtained by sentiment analysis. The predicted popularity pst is based upon the value of the selected type t and feature values of every shop type from selected circular area with radius r. In this way, for each shop type in the given location, first of all its popularity prediction is to be done. Then, as per the popularity values, all shop types are ranked in descending order and the shop types.

Autorentext

Abhijeet A. Chincholkar arbeitet als Assistenzprofessor in der Abteilung Elektronik und Telekommunikationstechnik des Jagadambha College of Engineering & Technology, Yavatmal. Er hat 10 Jahre Lehrerfahrung. Er erwarb seinen M.E.-Abschluss in Digitaler Elektronik an der S. G. B. Amravati Universität. Sein Interessengebiet ist die Bildverarbeitung.