Taking the decisions based on semantic net, in expert systems

机译：在专家系统中以语义网络为基础的决策

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N.O. Sokolova; L.F. Volyk;
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年度 2002
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1. A semantic social network-based expert recommender system [J] . Andrea Paramithiotti Computing reviews . 2014,第1期

机译：基于语义社交网络的专家推荐系统
2. Expert System and Semantic Web Knowledge Base for Low Frequency Electromagnetic Devices [J] . T. Mathialakan, S. Ratanajeevan H. Hoole Journal of Computational Intelligence and Electronic Systems . 2014,第4期

机译：低频电磁器件专家系统和语义网络知识库
3. A semantic social network-based expert recommender system [J] . Elnaz Davoodi, Keivan Kianmehr, Mohsen Afsharchi Applied Intelligence . 2013,第1期

机译：基于语义社交网络的专家推荐系统
4. Exploring Experts Decisions in Concrete Delivery Dispatching Systems Using Bayesian Network Learning Techniques [C] . Maghrebi Mojtaba, Waller S. Travis International conference on artificial intelligence, modelling and simulation . 2014

机译：利用贝叶斯网络学习技术探索混凝土配送系统中的专家决策
5. The potential for using expert systems techniques to facilitate the application of decision support systems in logistics network design and optimization. [D] . Lee, Hunsoo. 1991

机译：使用专家系统技术来促进决策支持系统在物流网络设计和优化中的应用潜力。
6. Knowledge-Based Systems. Methods for Developing and Evaluating Expert Systems: Closing the Loop on Diagnostic Decision Support Systems [O] . PL Elkin, GO Barnett, KT Famiglietti, 1990

机译：基于知识的系统。开发和评估专家系统的方法：封闭诊断决策支持系统上的循环
7. We develop a model of scientific creativity and test it in the field of rare diseases. Our model is based on the results of an in-depth case study of the Rett syndrome. Archival analysis, bibliometric techniques and expert surveys are combined with network analysis to identify the most creative scientists. First, alternative measures of generative and combinatorial creativity are compared. Then, we generalize our results and present a stochastic model of socio-semantic network evolution. The model predictions are tested with multiple networks of rare disease specialties. We find that new scientific collaborations among experts in a field enhance combinatorial creativity. Instead, high entry rates of novices are negatively related to generative creativity. By extending the set of useful concepts, creative scientists gain in centrality. At the same time, by increasing their centrality in the scientific community, scientists can replicate and generalize their results, thus contributing to a scientific paradigm. [O] . Massimo Riccaboni, Maria Laura Frigotto 100

机译：我们开发了一种科学创造力模型，并在稀有疾病领域进行测试。我们的模型基于对Rett综合征的深入案例研究的结果。档案分析，文献计量技术和专家调查与网络分析相结合，以确定最具创造力的科学家。首先，比较生成和组合创造力的替代措施。然后，我们推广了我们的结果，并提出了社会语义网络演化的随机模型。模型预测用多个罕见疾病专业网络进行测试。我们发现，一个领域的专家之间的新的科学合作增强了组合创造力。相反，新手的高入门率与生成创造力负相关。通过扩展这组有用的概念，创造性的科学家获得了中心地位。同时，通过增加科学界的中心地位，科学家们可以复制和推广他们的结果，从而促进科学范式的发展。
8. Computer Based Intelligence Support: An Integrated Expert System and Decision Support Systems Approach [R] . Sage, A. P., Lagomasino, A. 1988

机译：基于计算机的情报支持：综合专家系统和决策支持系统方法

Taking the decisions based on semantic net, in expert systems

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