Z Ehghaghi Kakoli
Toward a functional ontology of reputation for e-commerce
Ehghaghi Kakoli, Z; Nematbakhsh, MA; Saraee, MH
Abstract
In recent years, the expansion of the internet has influenced all aspect of our lives. Trust is an important factor making business transactions possible. In a conventional setting this trust is based on all involved parties knowing each other. However this is not true for business transactions which are handled online as parties are kept anonymous. To solve this shortcoming many reputation mechanisms have been reported in the literature but as each approach has its own concepts and terminology, transferring reputation is not possible among different approaches. In this paper, a functional ontology
for reputation in the field of electronic commerce is proposed to solve this problem. The proposed technique contains three main concepts, namely: entity, context and feedback. The aim of this work is to present a unit concept for reputation in the field of e-commerce and to collect extensive knowledge about reputation in this field and finally to present this knowledge to a structured format.
Citation
Ehghaghi Kakoli, Z., Nematbakhsh, M., & Saraee, M. (2011, March). Toward a functional ontology of reputation for e-commerce. Presented at e-Society 2011, 9th International Conference IADIS, Avila, Spain
Presentation Conference Type | Other |
---|---|
Conference Name | e-Society 2011, 9th International Conference IADIS |
Conference Location | Avila, Spain |
Start Date | Mar 10, 2011 |
End Date | Mar 13, 2011 |
Publication Date | Jan 1, 2011 |
Deposit Date | Aug 13, 2018 |
Related Public URLs | http://esociety-conf.org/ |
Additional Information | Event Type : Conference |
You might also like
Features in extractive supervised single-document summarization: case of Persian news
(2024)
Journal Article
Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips
(2023)
Journal Article
DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy
(2022)
Journal Article
Machine learning-based optimized link state routing protocol for D2D communication in 5G/B5G
(2022)
Presentation / Conference
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search