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排序方式: 共有296条查询结果,搜索用时 15 毫秒
1.
Bitmap indexes are commonly used in data warehousing applications such as on-line analytic processing (OLAP). Storing the bitmaps in compressed form has been shown to be effective not only for low cardinality attributes, as conventional wisdom would suggest, but also for high cardinality attributes. Compressed bitmap indexes, such as Byte-aligned Bitmap Compression (BBC), Word-Aligned Hybrid (WAH) and several of their variants have been shown to be efficient in terms of both time and space, compared to traditional database indexes. In this paper, we propose a new technique for compressed bitmap indexing, called Super Byte-aligned Hybrid (SBH) bitmap compression, which improves upon the current state-of-the-art compression schemes. In our empirical evaluation, the query processing time of SBH was about five times faster than that of WAH, while the size of its compressed bitmap indexes was retained nearly close to that of BBC. 相似文献
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金小峰 《计算机工程与应用》2011,47(7):143-145
分析了潜在语义模型,研究了潜在语义空间中文本的表示方法,提出了一种大容量文本集的检索策略。检索过程由粗粒度非相关剔除和相关文本的精确检索两个步骤组成。使用潜在语义空间模型对文本集进行初步的筛选,剔除非相关文本;使用大规模文本检索方法对相关文本在段落一级进行精确检索,其中为了提高检索的执行效率,在检索算法中引入了遗传算法;输出这些候选的段落序号。实验结果证明了这种方法的有效性和高效性。 相似文献
5.
隐含语意索引(LSI)是一个能有效捕获文档中词的隐含语意特征的方法。然而,用该方法选择的特征空间对文本分类来说可能不是最适合的,因为这种方法按照词的变化排序特征,而没有考虑到分类能力。支持向量机(SVM)高度的泛化能力使它特别适用于高维数据例如文档的分类。为此提出基于支持向量机的特征提取方法用于选择适于分类的LSI特征。该方法利用SVM高度泛化的分类能力, 通过使用在每一个规则下训练的分类器的参数对第k个特征对反向平方分解面的贡献w2k的值进行估计。实验表明当需要比LSI更少的训练和测试时间时,该方法能够以更为紧凑的表示方式提高分类性能。 相似文献
6.
Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures 总被引:1,自引:0,他引:1
Eamonn Keogh Li Wei Xiaopeng Xi Michail Vlachos Sang-Hee Lee Pavlos Protopapas 《The VLDB Journal The International Journal on Very Large Data Bases》2009,18(3):611-630
Shape matching and indexing is important topic in its own right, and is a fundamental subroutine in most shape data mining
algorithms. Given the ubiquity of shape, shape matching is an important problem with applications in domains as diverse as
biometrics, industry, medicine, zoology and anthropology. The distance/similarity measure for used for shape matching must
be invariant to many distortions, including scale, offset, noise, articulation, partial occlusion, etc. Most of these distortions
are relatively easy to handle, either in the representation of the data or in the similarity measure used. However, rotation
invariance is noted in the literature as being an especially difficult challenge. Current approaches typically try to achieve
rotation invariance in the representation of the data, at the expense of discrimination ability, or in the distance measure,
at the expense of efficiency. In this work, we show that we can take the slow but accurate approaches and dramatically speed
them up. On real world problems our technique can take current approaches and make them four orders of magnitude faster without
false dismissals. Moreover, our technique can be used with any of the dozens of existing shape representations and with all
the most popular distance measures including Euclidean distance, dynamic time warping and Longest Common Subsequence. We further
show that our indexing technique can be used to index star light curves, an important type of astronomical data, without modification.
Reproducible Research Statement: All datasets and images used in this work are freely available at . 相似文献
7.
城网建设与改造的特点之一是变电所的小型化和采用电缆出线。本文对近几年城网建设和改造中遇到的变电和送电专业配合、变电所和电缆出线建设不同期、变电所周边现状和未来规划不一致、地下物和规划勘察资料不符、市政道路建设时已预埋进所过路管线、相序核查不准而造成的六种设计接口问题进行了分析,并逐一提出了解决办法。 相似文献
8.
针对适合互补结构网络信息特点的过滤机制进行研究,提出一种改进的用户兴趣模型,在研究内容过滤和协作过滤的基础上.建立适合互补结构网络的多级混合过滤系统。通过对多级混合过滤模型的实验,表明多级混合过滤模型克服了单独使用内容过滤或协作过滤方法的缺点,提高了过滤的准确度。 相似文献
9.
As organizations reach higher levels of business process management maturity, they often find themselves maintaining very large process model repositories, representing valuable knowledge about their operations. A common practice within these repositories is to create new process models, or extend existing ones, by copying and merging fragments from other models. We contend that if these duplicate fragments, a.k.a. exact clones, can be identified and factored out as shared subprocesses, the repository's maintainability can be greatly improved. With this purpose in mind, we propose an indexing structure to support fast detection of clones in process model repositories. Moreover, we show how this index can be used to efficiently query a process model repository for fragments. This index, called RPSDAG, is based on a novel combination of a method for process model decomposition (namely the Refined Process Structure Tree), with established graph canonization and string matching techniques. We evaluated the RPSDAG with large process model repositories from industrial practice. The experiments show that a significant number of non-trivial clones can be efficiently found in such repositories, and that fragment queries can be handled efficiently. 相似文献
10.
Current research in indexing and mining time series data has produced many interesting algorithms and representations. However,
the algorithms and the size of data considered have generally not been representative of the increasingly massive datasets
encountered in science, engineering, and business domains. In this work, we introduce a novel multi-resolution symbolic representation
which can be used to index datasets which are several orders of magnitude larger than anything else considered in the literature.
To demonstrate the utility of this representation, we constructed a simple tree-based index structure which facilitates fast
exact search and orders of magnitude faster, approximate search. For example, with a database of one-hundred million time
series, the approximate search can retrieve high quality nearest neighbors in slightly over a second, whereas a sequential
scan would take tens of minutes. Our experimental evaluation demonstrates that our representation allows index performance
to scale well with increasing dataset sizes. Additionally, we provide analysis concerning parameter sensitivity, approximate
search effectiveness, and lower bound comparisons between time series representations in a bit constrained environment. We
further show how to exploit the combination of both exact and approximate search as sub-routines in data mining algorithms,
allowing for the exact mining of truly massive real world datasets, containing tens of millions of time series. 相似文献