Mobile merchandise evaluation service using novel information retrieval and image recognition technology

Chi-Chun Lo, Ting-Huan Kuo, Hsu-Yang Kung*, Hsiang-Ting Kao, Chi-Hua Chen, Che-I Wu, Ding Yuan Cheng

*Corresponding author for this work

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Consumers' purchasing behavior has obviously changed in recent years with developments in social economics. This change has been evident in the decreased ratio of planned purchases but not in the increase of planned (or spontaneous) purchases. This act of spontaneous or otherwise unplanned purchasing is called "impulse buying". However, buying under these conditions costs more money always comes with negative responses, such as complaints and regret. Therefore, we propose and have designed a new merchandise recommendation system, the Mobile Merchandise Evaluation Service Platform (MMESP). This is a three-tier system composed of Real-time Merchandise Identifying System (RMIS), Real-time Merchandise Evaluation System (RMES), and Real-time Merchandise Recommendation System (RMRS). With this system, Mobile Users (MUs) take pictures of merchandise and send them to MMESP. RMIS integrates Region Adjacency Graph (RAG) and Self-Organizing Maps (SOM) to gather information on the merchandise through those photographs, and. RMES and RMRS provide Intelligence Agents (IAs) and Multiple Document Summarization (MDS) to summarize recommendations on merchandise for MUs, all in real time. (C) 2010 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)120-128
JournalComputer Communications
Volume34
Issue number2
DOIs
StatePublished - 15 Feb 2011

Keywords

  • Information retrieval; Region adjacency graph; Self-organizing maps; Multiple document summarization; Mobile device

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