近年来领域本体的应用新进展

近年来,领域本体的发展非常迅速,不仅得到了广泛的应用,在实际应用中也取得了积极的作用。通过查找ISI、Elsevier等数据库查询到,近两年来国外文献中涉及的领域本体,包括化学领域、生物领域（分为基因领域和生物医学领域）、地理学领域和其他领域,并选取其中有代表性的领域本体并对其应用及进展进行分析研究,总结出领域本体应用进展的特点：涉及学科领域广;更加专业化、针对性更强;涉及多个学科的领域本体增多。领域本体的建设发展将有力推动数字图书馆的进步。     

Folksonomy模式中紧密型领域知识群落动态演化研究

具有高度感知易用性的Folksonomy知识组织模式,在实践应用中却呈现离散纷杂的外在表象。对Folksonomy知识组织模式中领域知识群落及其结构关系的研究,对于洞悉领域知识发展过程中的衍生、交叉、融合等现象具有重要意义。本研究以复杂网络分析中的层次派系分析技术为主要研究方法,基于标签共同标注关系构建领域知识网络。从标签间关联关系出发,对特定领域知识网络中紧密型知识群落的发展过程进行时间序列的动态跟踪与分析。研究结果表明:标签数量在领域成熟期趋于饱和,但标签间的连线数量却持续增长,紧密型领域知识群落规模逐渐扩大;紧密型领域知识群落数量总体递增的同时也存在波动,这种波动与知识群落自身的扩张、衰减、派生、融合的演化过程有关;随着领域知识的发展,紧密型知识群落之间的交叠密度呈上升趋势,并基于交叠关系形成了一个更大的知识群落,成为领域知识网络的部分骨架结构,进而能够展示出多个主要发展方向。对领域知识群落演化规律的揭示,有助于把握领域知识演进的发展脉络,并揭示Folksonomy知识组织模式中领域知识的发展模式与规律。     

Parallel programming characteristics of a DSP-based parallel system

INTRODUCTION DSP-based parallel system is a kind of high- performance parallel computer which uses parallel accelerating boards based on SHARC DSP chip (Kuo and Gan, 2005) as plug-in boards and inserts them into the military reinforcing computer, military fault-tolerant computer, even the personal computer. The parallel accelerating board based on SHARC DSP is a high-performance parallel processing board-level product developed by the Wuhan Digital Engineering Institute and is su…     

Applying the model driven generative domain engineering method to develop self-organizing architectural solutions for mobile robot

INTRODUCTION Model driven generative domain engineering (MDGDE) is improved on the basis of generative programming (Czarnecki and Ulrich, 2000) for the purpose of benefiting from the new emerging soft- ware engineering methods, such as agent oriented software engineering (Wooldridge, 1997), model driven architecture (MDA) (Kleppe et al., 2003) and aspect-oriented software development (AOSD) (Filman et al., 2004), etc. Agents are regarded as some special objects having more autonomy,…     

数学中常用的5种转化思想

文章介绍了数学中常用的5种转化思想及具体的转化方法。     

A comparative study of automated legal text classification using random forests and deep learning

Automated legal text classification is a prominent research topic in the legal field. It lays the foundation for building an intelligent legal system. Current literature focuses on international legal texts, such as Chinese cases, European cases, and Australian cases. Little attention is paid to text classification for U.S. legal texts. Deep learning has been applied to improving text classification performance. Its effectiveness needs further exploration in domains such as the legal field. This paper investigates legal text classification with a large collection of labeled U.S. case documents through comparing the effectiveness of different text classification techniques. We propose a machine learning algorithm using domain concepts as features and random forests as the classifier. Our experiment results on 30,000 full U.S. case documents in 50 categories demonstrated that our approach significantly outperforms a deep learning system built on multiple pre-trained word embeddings and deep neural networks. In addition, applying only the top 400 domain concepts as features for building the random forests could achieve the best performance. This study provides a reference to select machine learning techniques for building high-performance text classification systems in the legal domain or other fields.     

“C++程序设计”领域本体构建研究

根据教学规律和教学系统化设计理论,提出一种适用于教学领域的本体构建方法——ISD本体构建方法。该方法系统性强,融合学科教学特点。使用该方法成功构建了"C++程序设计"双语课程资源本体库,解决了实际知识向形式化编码的转化等问题,使本体的重用成为可能。     

基于小波变换图像增强的研究与分析

本文基于小波变换的理论,对图像进行增强分析,并与频域法的低通滤波和高通滤波以及空域法的平滑滤波、锐化滤波进行比较,表明小波变换对改善图像质量较好。     

关于行列式两个命题的证明

本文对行列式的两个命题给出了一种将行列式中若干元素用未定元素代入的证明方法。这种方法对行列式求值也很有用。     

基于复数平均相关调序的频域乐音盲分离

为解决频城内卷积混合乐音盲分离存在的顺序不确定问题,提出了基于频带间复数平均相关的调序算法,对每个频带的分离子信号进行顺序调整。仿真实验结果验证了该算法的有效性,与已有的基于幅值相关和能量相关的调序方法相比,其分离性能更优。