宴席上菜顺序商榷

宴席是人们日常饮食的重要组成部分，无论中餐宴席还是西餐宴席，上菜顺序都有一定规范，但有待完善。根据食物营养成分和饮食保健理论，宴席的科学合理的上菜顺序是：水果、汤莱、蔬菜与主食、荤菜。     

基于Milter实现的中文垃圾邮件过滤系统

提出一种基于内容的中文垃圾邮件实时过滤系统的实现方案，该系统建立在Linux的Sendmail邮件服务器上，通过Milter接口实时提取邮件内容，并结合中文分词及文本分类算法对邮件实施分类和过滤。该系统可嵌入多种文本分类算法，具有良好的可扩展性。通过测试对该系统内嵌入的不同分类算法模型进行了分析和比较。     

基于线性调频信号的多频测距算法

分析了基于线性调频信号多频测距时出现的二次相位问题,提出了利用测速系统速度信息进行相位消除的方法.对于测距中出现的模糊问题,利用了中国余数定理(孙子定理)来解决.与传统算法相比,该算法具有简单、实现方便、测距精度高等特点.给出了仿真结果,表明该算法具有较高的测距精度.     

基于统计和规则的末登录词识别方法研究

介绍了一种基于统计和规则的未登录词识别方法。该方法分为2个步骤：（1）对文本进行分词，对分词结果中的碎片进行全切分生成临时词典，并利用规则和频度信息给临时词典中的每个字串赋权值，利用贪心算法获得每个碎片的最长路径，从而提取未登录词；（2）在上一步骤的基础上，建立二元模型，并结合互信息来提取由若干个词组合而成的未登录词（组）。实验证明该方法开放测试的准确率达到81．25％，召回率达到82．38％。     

一种基于L_1范数模型和内点理论的潮流算法

提出一种结合L1范数模型和内点理论的潮流计算方法,利用基于扰动KKT条件的原始-对偶内点算法进行一般潮流问题求解.与以前的最小潮流法相比,该方法简单、求解易于收敛、易于程序实现,便于对病态系统求解,并同时能判断潮流方程是否有解.     

Text feature selection for sentiment classification of Chinese online reviews

In order to meet the requirement of customised services for online communities, sentiment classification of online reviews has been applied to study the unstructured reviews so as to identify users’ opinions on certain products. The purpose of this article is to select features for sentiment classification of Chinese online reviews with techniques well performed in traditional text classification. First, adjectives, adverbs and verbs are identified as the potential text features containing sentiment information. Then, four statistical feature selection methods, such as document frequency (DF), information gain (IG), chi-squared statistic (CHI) and mutual information (MI), are adopted to select features. After that, the Boolean weighting method is applied to set feature weights and construct a vector space model. Finally, a support vector machine (SVM) classifier is employed to predict the sentiment polarity of online reviews. Comparative experiments are conducted based on hotel online reviews in Chinese. The results indicate that the highest accuracy of the sentiment classification of Chinese online reviews is achieved by taking adjectives, adverbs and verbs together as the feature. Besides that, different feature selection methods make distinct performances on sentiment classification, as DF performs the best, CHI follows and IG ranks the last, whereas MI is not suitable for sentiment classification of Chinese online reviews. This conclusion will be helpful to improve the accuracy of sentiment classification and be useful for further research.     

基于字体的中文信息隐藏算法

为了将秘密信息嵌入到特定的载体之中,实现安全、高效的信息传输,以达到安全通信或版权保护等目的,针对中文文本设计了基于字体的信息隐藏算法.分析了文本信息隐藏的研究现状和存在的不足,根据不同的安全和嵌入率的需求,给出了3种对电子文本、打印文本、手写文本等皆适用的秘密信息嵌入算法,并且通过数学推导,对3种嵌入方式的嵌入率和嵌入效率等进行了分析比较.对算法的安全性进行了分析,并给出了增强安全性的手段.     

Semantic Role Labeling of Chinese Nominal Predicates with Dependency-Driven Constituent Parse Tree Structure

This paper explores a tree kernel based method for semantic role labeling （SRL） of Chinese nominal predicates via a convolution tree kernel. In particular, a new parse tree representation structure, called dependency-driven constituent parse tree （D-CPT）, is proposed to combine the advantages of both constituent and dependence parse trees. This is achieved by directly representing various kinds of dependency relations in a CPT-style structure, which employs dependency relation types instead of phrase labels in CPT （Constituent Parse Tree）. In this way, D-CPT not only keeps the dependency relationship information in the dependency parse tree （DPT） structure but also retains the basic hierarchical structure of CPT style. Moreover, several schemes are designed to extract various kinds of necessary information, such as the shortest path between the nominal predicate and the argument candidate, the support verb of the nominal predicate and the head argument modified by the argument candidate, from D-CPT. This largely reduces the noisy information inherent in D-CPT. Finally, a convolution tree kernel is employed to compute the similarity between two parse trees. Besides, we also implement a feature-based method based on D-CPT. Evaluation on Chinese NomBank corpus shows that our tree kernel based method on D-CPT performs significantly better than other tree kernel-based ones and achieves comparable performance with the state-of-the-art feature-based ones. This indicates the effectiveness of the novel D-CPT structure in representing various kinds of dependency relations in a CPT-style structure and our tree kernel based method in exploring the novel D-CPT structure. This also illustrates that the kernel-based methods are competitive and they are complementary with the feature- based methods on SRL.     

Effects of display method,text display rate and observation angle on comprehension performance and subjective preferences for reading Chinese on an LED display

This study examined the effects of display method, text display rate, and observation angle on comprehension performance and subjective preferences for Chinese characters presented on an LED display. The factors and levels studied were as follows: four text display methods (rapid serial visual presentation ‘RSVP’, leading, paged view scrolling, and continuous scrolling), three text display rates (160 characters per min ‘cpm’, 240 cpm, and 320 cpm), and seven observation angles (−75°, −60°, −30°, 0°, 30°, 60°, and 75°). The results indicated that a display rate of 160 cpm was in general superior to 240 and 320 cpm for comprehension scores and subjective evaluations. The effects of display method and observation angle were found to be non significant. However, there was a significant interaction between display method and display rate. The results of this study were used to make ergonomics recommendations applicable to LED displays for determining optimum dynamic text display methods for Chinese characters.     

汉藏短语对抽取中短语译文获取方法研究

该文从法律法规和公文领域汉藏语料中对待翻译汉语短语提取藏语译文。目前普遍采用的短语对抽取方法需要依赖于词性或句法分析等资源或词对齐技术。考虑现阶段藏文资源不足,词法句法相关技术不成熟,该文提出藏文词串频率统计方法(TSM)和藏文词序列相交算法(TIA)两种方法来获取藏语译文。其中TSM抽取1-1连续和非连续短语准确率达到90%左右,但遗漏1-n情况。TIA能够抽取1-n连续和非连续藏文语块,准确率达到81%。