Qinghua Zhu

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Qinghua Zhu is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Supporting group collaboration in Wiki by increasing the awareness of task conflict Comparative study
Design
Group collaboration
Online collaboration
Wiki
Aslib Proceedings: New Information Perspectives English 2013 Purpose: Wiki forms a new model of virtual collaboration. The original wiki is designed to hide content authorship information. Such design may hinder users from being aware of task conflict, resulting in low-efficient conflict management and decreased group performance. This study aims at increasing users' awareness of task conflict to facilitate wiki-based collaboration. Design/methodology/approach: A visual feedback dialog box is designed to increase users' awareness of task conflict. A survey-based comparative study is conducted by using original wiki and modified wiki (the new design). A total of 301 participants are invited. Structural equation model (SEM) is used to analyze survey data. Findings: Most users are willing to solve conflict issues, and the dialog box can increase users' awareness of task conflict. Conflict awareness can promote user's participation, gain better conflict resolution and improve group performance. The dialog box can enhance the influence of conflict awareness on user participation and conflict resolution, but reduce the influence of conflict awareness on group performance. Research limitations/implications: Only undergraduate students are invited, some typical variables are not included. The design needs improvement. Originality/value: A new wiki tool is designed. The influence of conflict awareness is explored while previous studies largely ignore this variable. 0 0
Incentivizing collaborative learning through visual feedback about conflict in Wiki Collaborative learning
Conflict
Design
Virtual collaboration
Wiki
CollaborateCom 2012 - Proceedings of the 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing English 2012 Conflict emerging from collaboration in wiki can be helpful to achieve a better quality of collaborative learning. However, few studies have utilized conflict to support collaborative learning and wiki systems themselves have limitations. This paper proposes to provide visual feedback about conflict in wiki based on the 'page history' to create a sense of audience, psychological ownership and support information seeking. Theoretical model is built upon literature, and the Partial Least Squares (PLS) results from a survey study (208 responses) indicate that conflict awareness can motivate students to participate, achieve better conflict resolution and improve the quality of learning. The results also show that the new design is well accepted by students and can significantly enhance the influence of conflict awareness on participation and conflict resolution. 0 0
The translation mining of the out of Vocabulary based on Wikipedia Cross-Language Information Retrieval
Out of vocabulary (OOV)
Target-deficit environment
Translation mining
Wikipedia
Jisuanji Yanjiu yu Fazhan/Computer Research and Development Chinese 2011 The query translation is one of the key factors that affect the performance of cross-language information retrieval (CLIR). In the process of querying, the excavation of the out of vocabulary (OOV) has the important significance to improve CLIRT. Out of Vocabulary means the words or phrase which can't be found in the dictionary. In this paper, according to Wikipedia data structure and language features, we divide translation environment into target-existence environment and target-deficit environment. Depending on the difficulty of translation mining in the target-deficit environment, we adopt the frequency change information and adjacency information to realize the extraction of candidate units, and compare common extraction methods of units. The results verify that our methods are more effective. We establish the strategy of mixed translation mining based on the frequency-distance model, surface pattern matching model and summary-score model, and add the model one by one, and then verify the function influence of each model. The experiments use the mining technique of OOV in search engine as baseline and then evaluate the results with TOP1. The results verify that the mixed translation mining method based on Wikipedia can achieve the correct translation rate of 0.6822, and the improvements on this method are 6.98% over the baseline. 0 0
Mining the Factors Affecting the Quality of Wikipedia Articles Web2.0
Wikipedia
Information quality
Neural Network
Quality Assessment
ISME English 2010 0 0
Mining the factors affecting the quality of Wikipedia articles Information quality
Neural network
Quality assessment
Web2.0
Wikipedia
Proceedings - 2010 International Conference of Information Science and Management Engineering, ISME 2010 English 2010 In order to observe the variation of factors affecting the quality of Wikipedia articles during the information quality improvement process, we proposed 28 metrics from four aspects, including lingual, structural, historical and reputational features, and then weighted each metrics in different stages by using neural network. We found lingual features weighted more in the lower quality stages, and structural features, along with historical features, became more important while article quality improved. However, reputational features did not act as important as expected. The findings indicate that the information quality is mainly affected by completeness, and well-written is a basic requirement in the initial stage. Reputation of authors or editors is not so important in Wikipedia because of its horizontal structure. 0 0