Difference between revisions of "Enhancing Wikipedia Management by Evaluation Agent System"
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| + | {{Infobox work | ||
| + | | title = Enhancing Wikipedia Management by Evaluation Agent System | ||
| + | | date = 2012 | ||
| + | | authors = [[Yue Qi]] | ||
| + | | doi = 10.4018/japuc.2012070104 | ||
| + | | link = https://dl.acm.org/citation.cfm?id=2434154 | ||
| + | }} | ||
'''Enhancing Wikipedia Management by Evaluation Agent System''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Yue Qi]]. | '''Enhancing Wikipedia Management by Evaluation Agent System''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Yue Qi]]. | ||
== Overview == | == Overview == | ||
Wikipedia has recently become a popular platform for knowledge sharing and creation. However, the enormously increasing amount of editing has caused management problems with efficiency, accuracy, and convenience for [[Wikipedia]] administrators. Therefore, this study aimed to develop an intelligent agent system based on Web 3.0, the evaluation agent system (EAS), to solve these problems. The EAS is characterized by hybrid Web techniques, [[artificial intelligence]], integration of management guidelines, retrieval of real-time information, and the transfer of cross-platform data and includes the following three systems: the testing agent, the wiki agent, and the rule-based expert system (RBES) agent. Because the RBES was central to the EAS, 29 university students were included in the study to examine the effectiveness of the RBES compared to the conventional approach to administration. The findings revealed that the RBES was better than the conventional approach in accuracy, efficiency, operation convenience, and fatigue strength. | Wikipedia has recently become a popular platform for knowledge sharing and creation. However, the enormously increasing amount of editing has caused management problems with efficiency, accuracy, and convenience for [[Wikipedia]] administrators. Therefore, this study aimed to develop an intelligent agent system based on Web 3.0, the evaluation agent system (EAS), to solve these problems. The EAS is characterized by hybrid Web techniques, [[artificial intelligence]], integration of management guidelines, retrieval of real-time information, and the transfer of cross-platform data and includes the following three systems: the testing agent, the wiki agent, and the rule-based expert system (RBES) agent. Because the RBES was central to the EAS, 29 university students were included in the study to examine the effectiveness of the RBES compared to the conventional approach to administration. The findings revealed that the RBES was better than the conventional approach in accuracy, efficiency, operation convenience, and fatigue strength. | ||
Revision as of 08:55, 21 May 2020
Authors | Yue Qi |
|---|---|
Publication date | 2012 |
DOI | 10.4018/japuc.2012070104 |
Links | Original |
Enhancing Wikipedia Management by Evaluation Agent System - scientific work related to Wikipedia quality published in 2012, written by Yue Qi.
Overview
Wikipedia has recently become a popular platform for knowledge sharing and creation. However, the enormously increasing amount of editing has caused management problems with efficiency, accuracy, and convenience for Wikipedia administrators. Therefore, this study aimed to develop an intelligent agent system based on Web 3.0, the evaluation agent system (EAS), to solve these problems. The EAS is characterized by hybrid Web techniques, artificial intelligence, integration of management guidelines, retrieval of real-time information, and the transfer of cross-platform data and includes the following three systems: the testing agent, the wiki agent, and the rule-based expert system (RBES) agent. Because the RBES was central to the EAS, 29 university students were included in the study to examine the effectiveness of the RBES compared to the conventional approach to administration. The findings revealed that the RBES was better than the conventional approach in accuracy, efficiency, operation convenience, and fatigue strength.
