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Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection

Computer Systems Science & Engineering 2022年第8期42卷 751-777页

作者： Komal Bashir Mariam Rehman Afnan Bashir Faria Kanwal Department of Computer Science Lahore College for Women UniversityLahore54000Pakistan Department of Information Technology Government CollegeFaisalabad54000Pakistan Engage Research Lab School of Law and SocietyUniversity of the Sunshine CoastSippy DownsQLD 4556Australia

Knowledge Management(km)has become a dynamic concept for inquiry in *** management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline,several km frameworks have been designed to serve this *** research aims to propose a Collaborative Knowledge Management(Ckm)Framework that bridges gaps and overcomes weaknesses in existing *** paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan.A software LCWU akmS was developed which serves as a practical implementation of the concepts behind the proposed CkmF *** akmS served as an effective system for rice leaf disease detection and *** aimed to enhance Ckm through knowledge sharing,lessons learned,feedback on problem resolutions,help from co-workers,collaboration,and helping *** were collected from 300 rice crop farmers by questionnaires based on *** olfman model was used to estimate the effectiveness of *** tests were performed including frequency measures of variables,Cronbach’s alpha reliability,and Pearson’s *** research provided a kmS depicting km and collaborative *** disease detection module was evaluated using the precision and recall method and found to be 94.16%*** system could replace the work of extension agents,making it a cost and time-effective initiative for farmer betterment.

关键词： Collaborative knowledge management framework jennex olfman km success model knowledge management rice disease detection

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