Personalized Knowledge Service Research Articles

Knowledge recommendation for workplace learning: a system design and evaluation perspective

PurposeAlthough digitalization in the workplace is burgeoning, tools are needed to facilitate personalized learning in informal learning settings. Existing knowledge recommendation techniques do not account for dynamic and task-oriented user preferences. The purpose of this paper is to propose a new design of a knowledge recommender system (RS) to fill this research gap and provide guidance for practitioners on how to enhance the effectiveness of workplace learning.Design/methodology/approachThis study employs the design science research approach. A novel hybrid knowledge recommendation technique is proposed. An experiment was carried out in a case company to demonstrate the effectiveness of the proposed system design. Quantitative data were collected to investigate the influence of personalized knowledge service on users’ learning attitude.FindingsThe proposed personalized knowledge RS obtained satisfactory user feedback. The results also show that providing personalized knowledge service can positively influence users’ perceived usefulness of learning.Practical implicationsThis research highlights the importance of providing digital support for workplace learners. The proposed new knowledge recommendation technique would be useful for practitioners and developers to harness information technology to facilitate workplace learning and effect organization learning strategies.Originality/valueThis study expands the scope of research on RS and workplace learning. This research also draws scholarly attention to the effective utilization of digital techniques, such as a RS, to support user decision making in the workplace.

Big data application framework and its feasibility analysis in library

PurposeThe purpose of this study is to introduce the concept of big data and provide a comprehensive overview to readers to understand big data application framework in libraries.Design/methodology/approachThe authors first used the text analysis and inductive analysis method to understand the concept of big data, summarize the challenges and opportunities of applying big data in libraries and further propose the big data application framework in libraries. Then they used questionnaire survey method to collect data from librarians to assess the feasibility of applying big data application framework in libraries.FindingsThe challenges of applying big data in libraries mainly include data accuracy, data reduction and compression, data confidentiality and security and big data processing system and technology. The opportunities of applying big data in libraries mainly include enrich the library database, enhance the skills of librarians, promote interlibrary loan service and provide personalized knowledge service. Big data application framework in libraries can be considered from five dimensions: human resource, literature resource, technology support, service innovation and infrastructure construction. Most libraries think that the big data application framework is feasible and tend to apply big data application framework. The main obstacles to prevent them from applying big data application framework is the human resource and information technology level.Originality/valueThis research offers several implications and practical solutions for libraries to apply big data application framework.

The Problem-Solving Agricultural Knowledge Service System for Farm Households

With the advancement of agricultural modernization of China, farmer’s demand of agricultural service has turned from the traditional agricultural information service to the problem-solving mode gradually. Professional, personalized knowledge service is required. How to use Internet-thinking to construct problem-solving agricultural science and technology knowledge service system which is used to solve all kinds of problems in the process of agricultural production for farmers is the core content of our development. In this paper, system architecture and some major function features are introduced. Through the running of the system, the problems in the system are analyzed and the optimal solutions are proposed. Scientific and technological progress and innovation is the guarantee of the sustainable development of agriculture. With the advance of agricultural modernization, demand of china farmers of agricultural science and technology service has from the traditional agricultural information services, gradually turned to the purpose of problem-solving mode. How to effectively use the mobile Internet to provide fast, efficient, professional and personalized service for the majority of farmers, break the agricultural expert system affiliation, bring together experts in different fields to realize agricultural experts and farmers 24 hours face-to-face information interaction, realize the precision agriculture technology service, effectively solve the problem of farmers’ fields of production is the core content of the development of this system.

Personalized E- learning System Based on Intelligent Agent

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

Personalized Knowledge Service Platform for Postgraduate: Based on Wiki System in Cloud Computing Environment

Personalized Knowledge Service Platform for Postgraduate: Based on Wiki System in Cloud Computing Environment