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1.
We evaluate author impact indicators and ranking algorithms on two publication databases using large test data sets of well-established researchers. The test data consists of (1) ACM fellowship and (2) various life-time achievement awards. We also evaluate different approaches of dividing credit of papers among co-authors and analyse the impact of self-citations. Furthermore, we evaluate different graph normalisation approaches for when PageRank is computed on author citation graphs.We find that PageRank outperforms citation counts in identifying well-established researchers. This holds true when PageRank is computed on author citation graphs but also when PageRank is computed on paper graphs and paper scores are divided among co-authors. In general, the best results are obtained when co-authors receive an equal share of a paper's score, independent of which impact indicator is used to compute paper scores. The results also show that removing author self-citations improves the results of most ranking metrics. Lastly, we find that it is more important to personalise the PageRank algorithm appropriately on the paper level than deciding whether to include or exclude self-citations. However, on the author level, we find that author graph normalisation is more important than personalisation.  相似文献   
2.
University ranking or higher education assessment in general has been attracting more and more public attention over the years. However, the subjectivity-based evaluation index and indicator selections and weights that are widely adopted in most existing ranking systems have been called into question. In other words, the objectivity and impartiality of those rankings has been worrisome. To address these concerns, this paper presents a quantitative and model-driven approach to acquiring the evaluation index and indicator weights in the US News & World Report ranking system. Structural equation modelling will be applied to mine non-subjective weights from collected data. The proposed approach will be validated using two groups of United States universities, National Universities and Liberal Arts Colleges, classified by the US News & World Report. Managerial and administrative implications will also be explored. This study shows a very promising future because it opens a new venue for the scholars and practitioners in the higher education assessment field to develop a real-time, scalable and model-driven higher education ranking system.  相似文献   
3.
我国大学排行研究与实践的进展及评析   总被引:5,自引:0,他引:5  
大学排行在传统上属于社会评估范畴。近年来,由于多主体的参与与高校改革,大学排行的传统概念与实践逐渐发生着变化。大学排行应该围绕“大学发展”的核心指标展开,构建大学发展性排行指标与评估体系。因为只有大学发展了,才能满足多方需求,更好地实现大学排行多种功能。  相似文献   
4.
20世纪90年代以来,我国的大学排名活动开展得有声有色,在国内甚至国际有一定影响的大学排名已经有5家。大学排名活动已经成为我国高校评估领域一支不可忽视的力量。同时,对大学排名的研究工作也一直没有停止过。各种有关大学排名的研究文章也构成了高等教育研究中的一个小热点。对有关文章的各种观点从比较、作用、质疑和建议等四个方面进行理论梳理与归纳总结。  相似文献   
5.
This paper proposes a simple, flexible, axiom-based mechanism for facilitating the comparison between a scholar's citation count and the visibility of the journals wherein the scholar's articles were published. The goal is to help research review bodies easily grasp the distinction these two forms of scholarly accomplishment and to provide a transparent way to articulate expectations about them to scholars. The approach is demonstrated using a widely applied and cooperative functional form that can reflect, via different parameter values, a wide range of possible beliefs about the relative merits of citation counts and journal visibility.  相似文献   
6.
高等教育产品属于准公共产品,但各层次、各类别高校、各专业产品公共性是有区别的。个人高等教育选择依据其高等教育的私人产品性质而做出,在现有中国高等教育入学选拔制度下,最能反映高等教育私人产品性质的是各高校及专业选择性指标的高低,这可以从报考志愿拥挤度和录取分数得以反映。高等教育学生资助,首先应依据申请学生所在学校、专业的选择性指标对学生进行分类,实施以政府资助为主或是以市场、学校资助为主。其次应对贫困学生进行分级,学生学习生活每月消费支出(参考最低生活保障标准)、所学专业类型、家庭所在位置(城乡、区域)、学生交纳学费情况、家庭成员职业背景、家庭或成员特殊情况等指标最能反映经济困难程度,应根据这些指标计算出个体的贫困指数,对资助主体实施不同级别的资助。再次应完善学生资助对象认定路径,要加大非诚信者的机会成本、建立资助信息平台、完善市场化资助主体认定资助对象的相关政策、细化资助对象认定的具体措施。  相似文献   
7.
宋代东宫权力的削减是伴随着宋代皇权发展而来的,东宫官职的阶官化、东宫率府的失职表明宋代皇权专制主义的产生。应从整个宋代制度的核心层面着手,来探寻宋代东宫制度变化的深意。  相似文献   
8.
目前图书借阅排行的传统算法是仅按借阅次数排序,该算法存在某些热门图书可能会长期占据排行榜前列之不足。论文提出了新的图书借阅排行算法,该算法综合考虑了借阅次数、复本数、入藏日期和最近外借日期等影响因素,在保证了较好推荐效果的情况下,实现了自动淘汰的机制,解决了传统算法的不足。  相似文献   
9.
Automatic text summarization has been an active field of research for many years. Several approaches have been proposed, ranging from simple position and word-frequency methods, to learning and graph based algorithms. The advent of human-generated knowledge bases like Wikipedia offer a further possibility in text summarization – they can be used to understand the input text in terms of salient concepts from the knowledge base. In this paper, we study a novel approach that leverages Wikipedia in conjunction with graph-based ranking. Our approach is to first construct a bipartite sentence–concept graph, and then rank the input sentences using iterative updates on this graph. We consider several models for the bipartite graph, and derive convergence properties under each model. Then, we take up personalized and query-focused summarization, where the sentence ranks additionally depend on user interests and queries, respectively. Finally, we present a Wikipedia-based multi-document summarization algorithm. An important feature of the proposed algorithms is that they enable real-time incremental summarization – users can first view an initial summary, and then request additional content if interested. We evaluate the performance of our proposed summarizer using the ROUGE metric, and the results show that leveraging Wikipedia can significantly improve summary quality. We also present results from a user study, which suggests that using incremental summarization can help in better understanding news articles.  相似文献   
10.
通过对第 4、第 5、第 6届中国大学生运动会 (以下简称大运会 )田径比赛各单项前 8名运动员成绩的统计 ,运用系统科学的建模方法 ,建立多种大运会田径比赛成绩与名次的预测模型 ,从中优选最适合大运会田径比赛男、女各单项成绩与名次的预测模型 ;并以田径比赛实践中长期积累起来的各单项前 8名运动员成绩资料为鉴标 ,建立波动差计算公式。应用最优预测模型和波动差计算公式 ,可预测下一届大运会田径比赛的成绩与名次。依据此预测的成绩与名次可为各省、直辖市备战大运会田径比赛提供信息依据。此研究方法亦可为今后预测全运会、奥运会等田径比赛成绩与名次提供新思路、新方法  相似文献   
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