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1.
[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据,通过对灰色预测法在情报研究中的应用情况进行梳理,总结其在应用过程中存在的不足,为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献,从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述,总结当前情报研究中灰色预测法的应用所存在的问题,并提出改进建议。[结果/结论] 在方法应用上,已有研究主要采用数列灰预测,且模型集中在单变量灰色预测模型,根据预测对象不同,灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用,未来可根据预测对象特点及研究目标尝试不同的灰色预测方法,扩宽灰色预测法在其他方面的情报研究问题中的应用。  相似文献   
2.
Using PISA and PIAAC data from twelve OECD countries, we examine the gap in cognitive skills among immigrants and natives and evaluate how those differences have evolved over time. We also consider how demographics, family background and school quality explain the development of cognitive skills of young people with immigrant backgrounds. The results show, first, that some convergence in skills occurs between second-generation immigrants and natives over time. Second, demographics, family background and school quality variables all contribute to the achievement gaps across different groups.  相似文献   
3.
In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献   
4.
张蕊 《科教文汇》2020,(13):151-152
本研究采用表现性评价,对x幼儿园大班一个班级39名幼儿进行为期一年的发展性评价,在真实情境中对幼儿的发展状况作出连续性评价,获悉幼儿不同阶段的发展状况,同时对评价过程进行总结和反思。  相似文献   
5.
[目的/意义] 通过构建二模复杂网络模型,揭示隐藏在海量文献中的隐性知识。[方法/过程] 通过NetworkX复杂网络工具包,依据任意两个节点的共现关系构建二模复杂网络模型;对网络模型中节点的共现关系进行加权,计算网络的拓扑信息并进行AP聚类,提取节点间的直接关系;采用AUC方法对AA、JC、加权改进的wAA和wJC等4种链路预测算法进行评价,遴选出最合适的预测算法,并对复杂网络的隐性关系进行预测分析。[结果/结论] 以潜在药物靶点挖掘为例进行的实证研究结果表明,wAA链路预测算法为最优的链路预测算法;二模复杂网络模型、指标和方法体系在美国化学文摘社数据库中的药物靶点挖掘中具有一定的有效性。下一步计划在其他数据库中或其他研究领域中进行尝试,以进一步验证该模型的通用性和有效性。  相似文献   
6.
Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).  相似文献   
7.
In the IR field it is clear that the value of a system depends on the cost and benefit profiles of its users. It would seem obvious that different users would prefer different systems. In the TREC-9 filtering track, systems are evaluated by a utility measure specifying a given cost and benefit. However, in the study of decision systems it is known that, in some cases, one system may be unconditionally better than another. In this paper we employ a decision theoretic approach to find conditions under which an Information Filtering (IF) system is unconditionally superior to another for all users regardless of their cost and benefit profiles.It is well known that if two IF systems have equal precision the system with better recall will be preferred by all users. Similarly, with equal recall, better precision is universally preferred. We confirm these known results and discover an unexpected dominance relation in which a system with lower recall will be universally preferred provided its precision is sufficiently higher.  相似文献   
8.
美国竞技体育"霸主"地位之透析   总被引:8,自引:0,他引:8  
通过查阅文献资料、访问调查、数理统计等方法 ,分析了美国参加奥运会以来的实力表现 ,在此基础上 ,对导致美国竞技体育霸主地位的因素——世界政治格局变化、西方文化精神、美国的社会分层结构、黑人的先天优势、高校竞技体育、发达的职业体育、科学化训练等进行了全面的论述 ,以为我国的竞技体育决策部门提供参考。  相似文献   
9.
以 2 0 0 1年全校初一新生为研究对象 ,通过对其性别、体质量、体育成绩的分析 ,科学阐述性别、体质量这2项因素与体育成绩的成因关系。结果表明 :性别、体质量对体育成绩的影响在统计学上具有非常显著和显著性的差异 (P <0 0 0 0 1,P =0 0 0 2 4)。女生成绩明显优于男生 (女生 =75 83± 10 71,男生 =67 72± 10 51) ,体质量位于中等和中上者的学生成绩相近 ,2组均优于上等组 (中等组 =74 2 4± 10 58,中上组 =73 87± 12 54,上等组 =68 60± 10 82 )。  相似文献   
10.
In Korean information retrieval, compound nouns play an important role in improving precision in search experiments. There are two major approaches to compound noun indexing in Korean: statistical and linguistic. Each method, however, has its own shortcomings, such as limitations when indexing diverse types of compound nouns, over-generation of compound nouns, and data sparseness in training. In this paper, we propose a corpus-based learning method, which can index diverse types of compound nouns using rules automatically extracted from a large corpus. The automatic learning method is more portable and requires less human effort, although it exhibits a performance level similar to the manual-linguistic approach. We also present a new filtering method to solve the problems of compound noun over-generation and data sparseness.  相似文献   
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