中文比较句识别及比较关系抽取

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。     

一种基于使用差异的词语领域性分析方法

领域知识的表达形式最终体现在词汇的领域性上,因此对领域词及其部件的领域度分析是一个关键。该文在分词的基础上,对各个领域语料进行分析,利用词语之间的关系,引入链接分析方法分析词语在各个领域中的使用重要性,并通过词语在各个领域中的使用差异性计算其领域度,从而达到领域分析的目的,获取某个领域的领域部件词。该文采用以上方法在军事、娱乐等领域进行了实验,实验结果表明该方法相对于当前常用的tf×idf方法和Bootstrapping方法,可以更有效地进行领域分析获取领域部件词。     

多进制基带信号功率谱密度的仿真分析

随着信息技术的发展,多进制数字基带信号的应用越来越广泛.而分析其频谱特性对多进制数字基带信号的应用十分必要.以二进制数字基带信号为基础,利用交变波和稳态波分解法首先分析了三进制数字基带信号的功率谱密度,然后推广分析了M(M≥2)进制数字基带信号的功率谱密度特性.最后分别选取二进制、三进制和四进制数字基带信号用Mat-hb平台仿真分析了其功率谱密度,结果显示多进制数字基带信号的频谱一般由离散谱和连续谱组成,但在特定的条件下,其频谱中将只存在连续谱成分,而不存在离散谱.仿真结果为多进制数字基带信号的分析和应用提供了有益的参考.     

基于信息融合技术的煤矿主通风机故障参数检测系统

针对目前煤矿主通风机故障诊断功能不完善、保障性措施不力等问题,文章提出了一种基于信息融合技术的煤矿主通风机故障参数检测系统的设计方案,简要分析了主通风机常见故障及信息融合技术,确定了故障参数检测方法,详细介绍了系统硬件及软件设计。实际应用表明,该系统实现了各故障参数的实时、在线检测,为主通风机的可靠运行提供了技术保障。     

基于H桥单元串联式多电平高压变频器在矿井提升机中的应用

针对某煤矿的主井提升机系统采用电动机转子串电阻调速方式存在运行损耗大的缺点,文章提出了一种对提升机电控系统进行H桥功率单元串联式多电平高压变频改造的方案,详细介绍了提升机PLC工艺控制系统的结构、主要技术特点以及变频传动系统实现的基本原理。实际应用表明,经改造后的矿井提升机高压变频系统运行稳定,完全达到了设计要求。     

一种新型软开关Buck变换器的研究

针对传统ZVT-PWM变换器的辅助开关硬关断的不足,提出了一种新型PWM控制的软开关Buck变换器方案,详细介绍了该新型软开关Buck变换器的拓扑结构及工作原理,并给出了具体的设计过程。新型软开关Buck变换器的辅助电路使主开关工作在零电压状态,所有的半导体器件均工作在软开关条件下,从而减小了开关损耗。仿真结果证明了该新型软开关Buck变换器方案的有效性。     

Pattern discovery and change detection of online music query streams

Mining of music data is one of the most important problems in multimedia data mining. In this paper, two research issues of mining music data, i.e., online mining of music query streams and change detection of music query streams, are discussed. First, we proposed an efficient online algorithm, FTP-stream (Frequent Temporal Pattern mining of streams), to mine all frequent melody structures over sliding windows of music melody sequence streams. An effective bit-sequence representation is used in the proposed algorithm to reduce the time and memory needed to slide the windows. An effective list structure is developed in the FTP-stream algorithm to overcome the performance bottleneck of 2-candidate generation. Experiments show that the proposed algorithm FTP-stream only needs a half of memory requirement of original melody sequence data, and just scans the music query stream once. After mining frequent melody structures, we developed a simple online algorithm, MQS-change (changes of Music Query Streams), to detect the changes of frequent melody structures in current user-centered music query streams. Two music melody structures (set of chord-sets and string of chord-sets) are maintained and four melody structure changes (positive burst, negative burst, increasing change and decreasing change) are monitored in a new summary data structure, MSC-list (a list of Music Structure Changes). Experiments show that the MQS-change algorithm is an effective online method to detect the changes of music melody structures over continuous music query streams.

From MPEG-7 user interaction tools to hanging basket models: bridging the gap

The content–user gap is the difference between the limited range of content-relevant preferences that may be expressed using the MPEG-7 user interaction tools and the much wider range of metadata that may be represented using the MPEG-7 content tools. One approach for closing this gap is to make the user and content metadata isomorphic by using the existing MPEG-7 content tools to represent user (as well as content) metadata (Agius and Angelides 2006, 2007). Subsequently, user preferences may be specified for all content, without omission. Since there is a wealth of user preference and history metadata within the MPEG-7 user interaction tools that can usefully complement these specific content preferences, in this paper we develop a method by which all user and content metadata may be bridged.

Using visual and text features for direct marketing on multimedia messaging services domain

Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience. Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.