全文获取类型
收费全文 | 48806篇 |
免费 | 1962篇 |
国内免费 | 1514篇 |
专业分类
电工技术 | 2851篇 |
技术理论 | 5篇 |
综合类 | 3399篇 |
化学工业 | 9811篇 |
金属工艺 | 1314篇 |
机械仪表 | 1861篇 |
建筑科学 | 4528篇 |
矿业工程 | 2382篇 |
能源动力 | 863篇 |
轻工业 | 4620篇 |
水利工程 | 1234篇 |
石油天然气 | 5152篇 |
武器工业 | 263篇 |
无线电 | 2799篇 |
一般工业技术 | 2866篇 |
冶金工业 | 2705篇 |
原子能技术 | 136篇 |
自动化技术 | 5493篇 |
出版年
2024年 | 69篇 |
2023年 | 217篇 |
2022年 | 621篇 |
2021年 | 892篇 |
2020年 | 909篇 |
2019年 | 488篇 |
2018年 | 445篇 |
2017年 | 706篇 |
2016年 | 830篇 |
2015年 | 975篇 |
2014年 | 2902篇 |
2013年 | 1977篇 |
2012年 | 3180篇 |
2011年 | 3337篇 |
2010年 | 3044篇 |
2009年 | 3024篇 |
2008年 | 2457篇 |
2007年 | 3511篇 |
2006年 | 3555篇 |
2005年 | 3395篇 |
2004年 | 2992篇 |
2003年 | 2827篇 |
2002年 | 2228篇 |
2001年 | 1930篇 |
2000年 | 1515篇 |
1999年 | 1100篇 |
1998年 | 824篇 |
1997年 | 591篇 |
1996年 | 466篇 |
1995年 | 400篇 |
1994年 | 250篇 |
1993年 | 172篇 |
1992年 | 132篇 |
1991年 | 93篇 |
1990年 | 41篇 |
1989年 | 38篇 |
1988年 | 42篇 |
1987年 | 23篇 |
1986年 | 10篇 |
1985年 | 12篇 |
1984年 | 6篇 |
1983年 | 8篇 |
1982年 | 8篇 |
1981年 | 9篇 |
1980年 | 4篇 |
1979年 | 3篇 |
1977年 | 4篇 |
1958年 | 2篇 |
1957年 | 2篇 |
1951年 | 2篇 |
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
991.
中文比较句识别及比较关系抽取 总被引:1,自引:0,他引:1
比较是一种具有一定说服力的评估方式,利用机器进行比较句的识别以及比较关系的抽取可以对观点挖掘、信息推荐等应用提供重要的依据。该文通过构建中文比较模式库以实现中文比较句的自动识别。在此基础上,该文通过选取比较主体、比较客体及其上下文的词、词性、位置、语义以及比较属性的领域知识等特征,利用条件随机域模型进行中文比较关系抽取。实验结果表明,中文比较模式库的构建有助于比较句的自动识别,而在词、词性、位置等Baseline特征中融入语义、领域知识及启发式规则特征后,基于条件随机域的比较关系抽取结果有了显著的提高。 相似文献
992.
基于Wikipedia的语义元数据生成 总被引:1,自引:0,他引:1
语义元数据提供数据的语义信息,在数据的理解、管理、发现和交换中起着极为重要的作用。随着互联网上数据爆炸式的增长,对自动元数据生成技术的需求也就变得更加迫切。获得目标语义元数据及得到足够的训练语料是使用自动生成技术的两个基本问题。由于获得目标语义元数据需要专家知识,而获得足够的训练语料需要大量的手工工作,这也就使得这两个问题在构建一个成功的系统时至关重要。该文基于Wikipedia来解决这两个问题通过分析一个类别中条目的目录表(table-of-contents)来抽取目标语义元数据,通过对分析文档结构和赋予目标结构正确的语义元数据来构建训练语料库。实验结果表明,该文的方法能够有效地解决这两个问题,为进一步的大规模的语义元数据应用系统打下了坚实的基础。 相似文献
993.
介词结构在汉语文本中出现频率很高,正确识别介词结构边界对句法分析、语音合成中的韵律短语划分有着重要意义。该文较为系统地探讨了汉语中常用介词的边界识别问题。利用支持向量机SVM模型,基于输出概率而不是简单的二分法来选择正确的后边界。探讨了不同的特征选择,并尝试加入语义信息等不同特征组合以提高识别准确率。对常用的68个介词进行边界识别实验,5折交叉验证的准确率达到90.95%,优于前人的识别结果。 相似文献
994.
该文提出了一种基于加权有限状态转化器(WFST)的多模型融合人名翻译框架。该框架以两个基于字符的转换模型和两个基于发音的转换模型为核心,通过加权有限状态转换器将多模型进行融合实现对人名的翻译。与单个模型相比,该文提出的方法的优势在于通过从各种信息源得到的数据价值的最大化。实验结果表明,基于多模型融合方法的人名翻译的错误率比单一模型的人名翻译的错误率降低了7.14%。 相似文献
995.
996.
997.
知识获取是制约基于语料库的词义消歧方法性能提高的瓶颈,使用等价伪词的自动语料标注方法是近年来解决该问题的有效方法。等价伪词是用来代替歧义词在语料中查找消歧实例的词。但使用等价伪词获得的部分伪实例质量太差,且无法为没有或很少同义词的歧义词确定等价伪词。基于此,该文提出一种将等价伪词获得的伪实例和人工标注实例相结合的词义消歧方法。该方法通过计算伪实例与歧义词上下文的句子相似度,删除质量低下的伪实例。并借助人工标注语料为某些无等价伪词的歧义词提供消歧实例,计算各义项的分布概率。在Senseval-3汉语消歧任务上的实验中,该文方法取得了平均F-值为0.79的成绩。 相似文献
998.
A.?Konstantinidis Th.?TsiatsosEmail author A.?Pomportsis 《Multimedia Tools and Applications》2009,44(2):279-304
E-learning systems have gone through a radical change from the initial text-based environments to more stimulating multimedia
systems. Such systems are Collaborative Virtual Environments, which could be used in order to support collaborative e-learning
scenarios. The main aim of this paper is to aid educational designers in selecting, designing and evaluating three dimensional
collaborative virtual environments in order to gain the pedagogical benefits of Computer Supported Collaborative Learning.
Therefore, this paper initially discusses the potential of three dimensional networked virtual environments for supporting
collaborative learning. Furthermore, based on a two-step platform selection process this paper (a) presents and compares three
dimensional multi-user virtual environments for supporting collaborative learning and (b) validates the most promising solution
against a set of design principles for educational virtual environments. According to these principles, an educational environment
has been implemented on top of the selected platform in order to support collaborative e-learning scenarios. The design of
this environment is also presented. In addition, this paper presents the results of three small scale studies carried out
in a tertiary education department, to assess the educational environment. This environment has been evaluated based on a
hybrid evaluation methodology for uncovering usability problems, collecting further requirements for additional functionality
to support collaborative virtual learning environments, and determining the appropriateness of different kinds of learning
scenarios.
相似文献
A. PomportsisEmail: |
999.
Mutation testing has traditionally been used as a defect injection technique to assess the effectiveness of a test suite as
represented by a “mutation score.” Recently, mutation testing tools have become more efficient, and industrial usage of mutation
analysis is experiencing growth. Mutation analysis entails adding or modifying test cases until the test suite is sufficient
to detect as many mutants as possible and the mutation score is satisfactory. The augmented test suite resulting from mutation
analysis may reveal latent faults and provides a stronger test suite to detect future errors which might be injected. Software
engineers often look for guidance on how to augment their test suite using information provided by line and/or branch coverage
tools. As the use of mutation analysis grows, software engineers will want to know how the emerging technique compares with
and/or complements coverage analysis for guiding the augmentation of an automated test suite. Additionally, software engineers
can benefit from an enhanced understanding of efficient mutation analysis techniques. To address these needs for additional
information about mutation analysis, we conducted an empirical study of the use of mutation analysis on two open source projects.
Our results indicate that a focused effort on increasing mutation score leads to a corresponding increase in line and branch
coverage to the point that line coverage, branch coverage and mutation score reach a maximum but leave some types of code
structures uncovered. Mutation analysis guides the creation of additional “common programmer error” tests beyond those written
to increase line and branch coverage. We also found that 74% of our chosen set of mutation operators is useful, on average,
for producing new tests. The remaining 26% of mutation operators did not produce new test cases because their mutants were
immediately detected by the initial test suite, indirectly detected by test suites we added to detect other mutants, or were
not able to be detected by any test.
Ben Smith is a second year Ph.D. student in Computer Science at North Carolina State University working as an RA under Dr. Laurie Williams. He received his Bachelor’s degree in Computer Science in May of 2007 and he hopes to receive his doctorate in 2012. He has begun work on developing SQL Coverage Metrics as a predictive measure of the security of a web application. This fall, he will be beginning the doctoral preliminary exam and working as a Testing Manager for the NCSU CSC Senior Design Center: North Carolina State’s capstone course for Computer Science. Finally, he has designed and maintained the websites for the Center for Open Software Engineering and ESEM 2009. Laurie Williams is an Associate Professor in the Computer Science Department of the College of Engineering at North Carolina State University. She leads the Software Engineering Reasearch group and is also the Director of the North Carolina State University Laboratory for Collaborative System Development and the Center for Open Software Engineering. She is also technical co-director of the Center for Open Software Engineering (COSE) and the area technical director of the Secure Open Systems Initiative (SOSI) at North Carolina State University. Laurie received her Ph.D. in Computer Science from the University of Utah, her MBA from Duke University, and her BS in Industrial Engineering from Lehigh University. She worked for IBM for nine years in Raleigh, NC before returning to academia. Laurie’s research interests include agile software development methodologies and practices, collaborative/pair programming, software reliability and testing, and software engineering for secure systems development. 相似文献
Laurie WilliamsEmail: |
Ben Smith is a second year Ph.D. student in Computer Science at North Carolina State University working as an RA under Dr. Laurie Williams. He received his Bachelor’s degree in Computer Science in May of 2007 and he hopes to receive his doctorate in 2012. He has begun work on developing SQL Coverage Metrics as a predictive measure of the security of a web application. This fall, he will be beginning the doctoral preliminary exam and working as a Testing Manager for the NCSU CSC Senior Design Center: North Carolina State’s capstone course for Computer Science. Finally, he has designed and maintained the websites for the Center for Open Software Engineering and ESEM 2009. Laurie Williams is an Associate Professor in the Computer Science Department of the College of Engineering at North Carolina State University. She leads the Software Engineering Reasearch group and is also the Director of the North Carolina State University Laboratory for Collaborative System Development and the Center for Open Software Engineering. She is also technical co-director of the Center for Open Software Engineering (COSE) and the area technical director of the Secure Open Systems Initiative (SOSI) at North Carolina State University. Laurie received her Ph.D. in Computer Science from the University of Utah, her MBA from Duke University, and her BS in Industrial Engineering from Lehigh University. She worked for IBM for nine years in Raleigh, NC before returning to academia. Laurie’s research interests include agile software development methodologies and practices, collaborative/pair programming, software reliability and testing, and software engineering for secure systems development. 相似文献
1000.
Project-based learning is a student-centered comprehensive instructional approach where students collectively engage themselves in complex learning tasks. Recent advances in educational technologies have made student-centered learning in a technology rich environment both possible and feasible. This paper will report part of a larger study carried out at a school in the United States of America on the use ofconstructivism and technology in project-based learning. Data collection techniques included those typically associated with qualitative field research. In this paper, the technological infrastructure of the school and how technology is used in one of the project-based learning classes will be provided. Based on this study, some suggestions are also provided on how technology can be used in the context of other countries including in Malaysia. 相似文献