File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Design intelligence of web application for internet direct consumer-to-consumer trading

TitleDesign intelligence of web application for internet direct consumer-to-consumer trading
Authors
KeywordsArtificial neural network
Data mining
Decision making
Online trading
Recommender systems
Used goods
Issue Date2015
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000363
Citation
The 2015 International Conference on Information Networking (ICOIN 2015), Siem Reap, Cambodia, 12-14 January 2015. In Conference Proceedings, 2015, p. 233-237 How to Cite?
AbstractAn online web application called Student-Trade has been developed. It is a state-of-the-art platform for direct consumer-to-consumer trading in the Internet. The platform is targeted for direct consumer-to-consumer trading among university students. The items for trading include books, household items, electronics, housing rental, sports equipment and tutoring services. This paper is on the design intelligence of the Student-Trade web application. One objective is to help the user to decide on the selling price of his item when the item is being posted in the web application. The system integrates a hybrid neighborhood search algorithm for determining the price of sale item when it is placed for trading in the Internet. Data mining techniques are explored for efficient processing of a vast amount of information in the database tables. In addition, the trading system would also have the intelligence of recommending items or products to a potential buyer given the previous purchase patterns. The aim is to provide a pleasant trading experience for the user. © 2015 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/214834
ISBN

 

DC FieldValueLanguage
dc.contributor.authorChan, V-
dc.contributor.authorWu, TH-
dc.contributor.authorPang, G-
dc.date.accessioned2015-08-21T11:58:02Z-
dc.date.available2015-08-21T11:58:02Z-
dc.date.issued2015-
dc.identifier.citationThe 2015 International Conference on Information Networking (ICOIN 2015), Siem Reap, Cambodia, 12-14 January 2015. In Conference Proceedings, 2015, p. 233-237-
dc.identifier.isbn978-1-4799-8342-1-
dc.identifier.urihttp://hdl.handle.net/10722/214834-
dc.description.abstractAn online web application called Student-Trade has been developed. It is a state-of-the-art platform for direct consumer-to-consumer trading in the Internet. The platform is targeted for direct consumer-to-consumer trading among university students. The items for trading include books, household items, electronics, housing rental, sports equipment and tutoring services. This paper is on the design intelligence of the Student-Trade web application. One objective is to help the user to decide on the selling price of his item when the item is being posted in the web application. The system integrates a hybrid neighborhood search algorithm for determining the price of sale item when it is placed for trading in the Internet. Data mining techniques are explored for efficient processing of a vast amount of information in the database tables. In addition, the trading system would also have the intelligence of recommending items or products to a potential buyer given the previous purchase patterns. The aim is to provide a pleasant trading experience for the user. © 2015 IEEE.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000363-
dc.relation.ispartofInternational Conference on Information Networking-
dc.rightsInternational Conference on Information Networking. Copyright © IEEE.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectArtificial neural network-
dc.subjectData mining-
dc.subjectDecision making-
dc.subjectOnline trading-
dc.subjectRecommender systems-
dc.subjectUsed goods-
dc.titleDesign intelligence of web application for internet direct consumer-to-consumer trading-
dc.typeConference_Paper-
dc.identifier.emailPang, G: gpang@eee.hku.hk-
dc.identifier.authorityPang, G=rp00162-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICOIN.2015.7057888-
dc.identifier.scopuseid_2-s2.0-84940518392-
dc.identifier.hkuros250196-
dc.identifier.spage233-
dc.identifier.epage237-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151008-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats