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《Information processing & management》2005,41(3):613-633
Signature files and inverted files are well-known index structures. In this paper we undertake a direct comparison of the two for searching for partially-specified queries in a large lexicon stored in main memory. Using n-grams to index lexicon terms, a bit-sliced signature file can be compressed to a smaller size than an inverted file if each n-gram sets only one bit in the term signature. With a signature width less than half the number of unique n-grams in the lexicon, the signature file method is about as fast as the inverted file method, and significantly smaller. Greater flexibility in memory usage and faster index generation time make signature files appropriate for searching large lexicons or other collections in an environment where memory is at a premium. 相似文献
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S.V.Nageswara Rao S.Sitharama Iyengar C.E.Veni Madhavan 《Information processing & management》1985,21(5):433-442
A variety of data structures such as inverted file, multi-lists, quad tree, k-d tree, range tree, polygon tree, quintary tree, multidimensional tries, segment tree, doubly chained tree, the grid file, d-fold tree. super B-tree, Multiple Attribute Tree (MAT), etc. have been studied for multidimensional searching and related problems. Physical data base organization, which is an important application of multidimensional searching, is traditionally and mostly handled by employing inverted file. This study proposes MAT data structure for bibliographic file systems, by illustrating the superiority of MAT data structure over inverted file. Both the methods are compared in terms of preprocessing, storage and query costs. Worst-case complexity analysis of both the methods, for a partial match query, is carried out in two cases: (a) when directory resides in main memory, (b) when directory resides in secondary memory. In both cases, MAT data structure is shown to be more efficient than the inverted file method. Arguments are given to illustrate the superiority of MAT data structure in an average case also. An efficient adaptation of MAT data structure, that exploits the special features of MAT structure and bibliographic files, is proposed for bibliographic file systems. In this adaptation, suitable techniques for fixing and ranking of the attributes for MAT data structure are proposed. Conclusions and proposals for future research are presented. 相似文献
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提出了一种利用同步双端口存储器IP和标准单元来实现嵌入式可编程存储器中的字宽配置的方案以降低设计的复杂性,提高设计效率. 通过寄存输出控制信号来优化嵌入式可编程存储器混合宽度配置的实现结构以增强读出数据的稳定性. 对比试验表明,优化后的结构还有利于提高复杂实现电路的性能. 该优化结构的嵌入式可编程存储器已在SMIC 0.18μm 1P6M CMOS工艺线上流片. 测试结果表明,其读出数据具有良好的稳定性,在读出时间方面与相近工艺、相同存储容量的采用全定制方法设计的商用嵌入式可编程存储器相当. 相似文献
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《Information processing & management》1987,23(3):225-238
Ergonomics Abstracts Retrieval System (EARS) is an online bibliographic information search and retrieval system using the hierarchical subject classification of the Ergonomics Abstracts. EARS is designed using an inverted file organization and is implemented on CDC-Cyber. The data base of abstracts is organized using a fixed-length record format, where each logical record corresponds to a variable number of fixed-length physical records. Accordingly, an index for the identification of physical records from the logical records is used. The data base is inverted on a three-level hierarchical classification scheme and postings files are used for data base inversion. The data base is accessed after selectively traversing a 4-layer structure of indexes and postings files. EARS provides facilities to perform combinations of searches, limited searches, and certain editing functions. The system is currently used extensively by the Western New York Human Factors research community. The logical and physical designs of EARS, its interactive operational features, and its current expansions are described in this paper. 相似文献
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应激会对动物的学习记忆能力产生影响,这种影响呈一种倒U型关系,即当应激强度过大或时间过长时这种影响往往是一种损伤,而适度的应激会对学习记忆产生促进作用。目前认为应激激活了下丘脑-垂体-肾上腺（hypothalamo-pituitary-adrenal,HPA）轴,诱导糖皮质激素的释放。适量的糖皮质激素会促进长时程增强（long-term potentiation,LTP）的形成,从而促进学习记忆。血清/糖皮质激素诱导激酶（serum and glucocorticoid regulated protein kinase,SGK）作为糖皮质激素诱导的一个激酶,参与了多种离子通道的调节,能够促进神经元的存活和轴突的再生。研究发现SGK的表达也会促进空间学习记忆能力。 相似文献
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基于有限理性和传染机制的金融资产定价模型 总被引：2，自引：0，他引：2
主要讨论基于有限理性和传染机制的资产定价模型，该模型包括：买价（卖价）的动态方程、目标价格的动态方程、买价（卖价）的连续微分方程的推导，市场价格的方程和一阶距和二阶矩方程，实现了从微观上市场参与者的特征到宏观上市场价格的有效转换，基于有限理论和传染机制的资产定价模型可以解释金融资产产的价格泡沫和波动率过大现象。 相似文献
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《Information processing & management》1986,22(3):243-250
This paper describes how the operations on the local inverted files are to be modified in order to use them in the distributed information retrieval system based on thesauri. The global system consists of n local retrieval systems. The presented retrieval rules may be viewed as the logical approach in implementing a physical distributed retrieval system. 相似文献
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传统的数学学习方法重点都建立在对数学技巧以及分析方法上,而往往忽略了记忆的重要性。记忆大量的数学知识是学好小学数学的关键,培养数学记忆的习惯显得尤为重要。师者应该帮助小学生培养良好的记忆思维,通过引导记忆开启小学生学习数学的记忆大门,为小学数学知识的接受奠定良好的基础。“死记硬背”也并非指毫无章法地强记,而是通过适当的方法长久记住,不易遗忘。 相似文献
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基于国家创新和数字化战略的考虑，各级政府不断加大数字化投入，力求提高区域创新水平，增强区域创新能力。目前，在区域数字化水平对创新绩效影响领域还缺乏相关实证研究成果，特别是县（区、市）层面的研究。基于此，本文采用2015-2017年浙江省73个县（区、市）的面板数据，从数字化接入、装备、平台建设、应用水平四个方面实证研究区域数字化水平对创新绩效的影响。实证研究结果表明：区域数字化接入水平的提高有利于提升创新绩效，区域数字化装备、平台建设、应用水平对创新绩效影响呈现倒U型关系。推进区域数字化建设有利于创新绩效的提高，但需注意协调在不同数字化投入方向上的资源投入不足和过度投入等问题。 相似文献
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XML与关系数据库数据的转换的研究 总被引：1，自引：0，他引：1
XML数据库等已经开始迅速发展．但是这些新挂术在现阶段仍然不很成熟，目前对XML数据的普遍处理方法是将其转换成关系格式，以便利用目前成熟的关系数据库枝术进行存储和查询。文章讨论了XML文档与关系型数据库之间的关系，并介绍了如何将XML文件数据与关系数据库数据转换的具体实现。 相似文献
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职高学生基础普遍比较差,大多数对学习提不起兴趣,记忆力虽正处于高峰期,但都不用心记忆。由于学习目的不明确、不懂得学习的重要性,他们只对自己感兴趣的事物有记忆力,对各种专业知识的学习兴趣不高。针对职高学生的特点及记忆的特点,作者在近20年的教学经验的基础上,始终积极探索如何让学生在课堂中愉悦地记住各种解剖学名词,在课堂中做了一些尝试,收到了一定的效果。 相似文献
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排序是数据处理中很重要的技术之一,冒泡排序是实现排序功能诸多方法中的一种。根据冒泡排序算法思想,讨论了4种算法,并在Visual Basic环境中实现。 相似文献
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中国股市的泡沫度问题一直是国内外学者关注的焦点,主要指出了传统股票定价方法的理论缺陷以及利用期权定价模型给股票定价的可行性,在此基础上提出了研究股票泡沫度的一种新的思路,建立了一个计算股票泡沫度的理论模型,最后举例说明了其可操作性。 相似文献
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房地产泡沫成因及其投机度测度研究 总被引：8，自引：1，他引：8
本文在解析房地产泡沫内涵的基础上，从投机、消费者预期有限性、房地产市场发育、金融体制完善性等方面对房地产泡沫的形成进行了剖析，特别指出过度投机导致的地价飞涨是房地产泡沫产生的最直接原因，建立了房地产投机泡沫的测度模型。并结合我国实际对模型进行了实证分析，对房地产泡沫的风险防范提出了建议。 相似文献
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《Information processing & management》2023,60(1):103109
With an increase in the number of data instances, data processing operations (e.g. clustering) requires an increasing amount of computational resources, and it is often the case that for considerably large datasets such operations cannot be executed on a single workstation. This requires the use of a server computer for carrying out the operations. However, to ensure privacy of the shared data, a privacy preserving data processing workflow involves applying an encoding transformation on the set of data points prior to applying the computation. This encoding should ideally cater to two objectives—first, it should be difficult to reconstruct the data, second, the results of the operation executed on the encoded space should be as close as possible to the results of the same operation executed on the original data. While standard encoding mechanisms, such as locality sensitive hashing, caters to the first objective, the second objective may not always be adequately satisfied.In this paper, we specifically focus on ‘clustering’ as the data processing operation. We apply a deep metric learning approach to learn a parameterized encoding transformation function with an objective to maximize the alignment of the clusters in the encoded space to those in the original data. We conduct experimentation on four standard benchmark datasets, particularly MNIST, Fashion-MNIST (each dataset contains 70K grayscale images), CIFAR-10 consisting of 60K color images and 20-Newsgroups containing 18K news articles. Our experiments demonstrate that the proposed method yields better clusters in comparison to approaches where the encoding process is agnostic of the clustering objective. 相似文献
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基于创新扩散的耐用品品牌扩散模型探析 总被引：1，自引：0，他引：1
基于创新扩散理论并依据耐用品品牌的市场特征,系统地提出了耐用品品牌的垄断品牌扩散模型、寡头品牌扩散模型、品牌竞争扩散模型和品牌竞争扩散一般模型;采用中国移动通信产业品牌的实际数据对前三个模型进行了验证。 相似文献
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基于国际元数据标准设计世界客都“古民居数字记忆工程”地方文化特色资源语义组织与元数据模型,以智能化知识服务为导向设置资源分类,基于内容特征关联设计资源开放获取机制,完成项目海量无序特色文化数字资源的有序组织与高效利用,实现元数据的国际化交换共享。 相似文献