Using LSA and text segmentation to improve automatic Chinese dialogue text summarization

Automatic Chinese text summarization for dialogue style is a relatively new research area. In this paper, Latent Semantic Analysis （LSA） is first used to extract semantic knowledge from a given document, all question paragraphs are identified, an automatic text segmentation approach analogous to Text＇filing is exploited to improve the precision of correlating question paragraphs and answer paragraphs, and finally some ＂important＂ sentences are extracted from the generic content and the question-answer pairs to generate a complete summary. Experimental results showed that our approach is highly efficient and improves significantly the coherence of the summary while not compromising informativeness.     

我国能源建设新构想

能源危机以及由于大量燃烧碳及烃类引起的环境问题,正在对现代社会构成越来越大的威胁。本文根据我国的资源实际,提出了发展液氨(LSA)燃料的设想,并与烃燃料和氢能源进行了比较。同时,对发展LSA燃料与推广洁净煤技术的结合进行了探讨。     

Intrathymic inoculation of donor liver specific antigen alleviates rejection of liver allotransplantation

Use and effects of liver specific antigen in orthotopic liver transplantations were researched in this study. Group I: syngeneic control (Wistar-to-Wistar); Group II: acute rejection (SD-to-Wistar); Group III: Thymic inoculation of SD rat LSA day 7 before transplantation. The observation of common situation and survival time, rejection grades, NF-κB activity of splenocytes and IL-2mRNA expression of grafted liver were used to analyze acute rejection severity and immune state of animals in different groups. The common situation of group I was very well after transplantation and no signs of rejection were found. Recipients of group II lost body weight progressively All dead within day 9 to day 13 posttransplantation; median survival time was 10.7 ±0.51 days. It was an optimal acute rejection control. As for group III, 5 out of 6 recipients survived for a long time and common situation was remarkably better than that of group II. Its rejection grades were significantly lower than that of group II(P<0.05). NF-κB activity was only detected in group I at day 5 and day 7 after transplantation, whereas high activity of NF-κB was detected at all time points in groupII and the low NF-κB activity detected in group III was significantly lower than that of group II (P<0.05). No IL-2mRNA expression was detected at any time point in group I, whereas high level expression was detected at all time points in group II and the low level expression only detected at day 3 in group III was significantly lower than that of group II (P<0.05). Conclusion: LSA is an important transplantation antigen which is involved directly in the immunorejection of liver transplantation. We report here for the first time that intrathymic inoculation of LSA can alleviate the rejection of liver allotransplantation; and that grafts can survive for a long time thereby, thus leading to a novel way to achieve liver transplantation immunotolerance. Project (NO. 011106206) supported by the Science and Technology Bureau of Zhejiang Province Foundation     

多层次web文本分类

传统的文本分类大多基于向量空间,分类体系为甲面体系,忽视了类别间的层次关系。根据LSA理论提出了一种多层次web文本分类方法。建立类模型时,根据类别的层次关系树由下到上逐层为具有相同父节点的类别建立一个类模型;分类时,由上到下,根据相应的类模型存LS空间上分类。这种分类方法解决了LSA模型中高维矩阵难以进行奇异值分解的问题。同时体现了web文本中词条的语义关系,注重了词条在网页中的表现形式。实验表明,多层次web文本分类方法比基于平面分类体系的分类方法在查全率和准确率方面要好。     

关于OSPF路由优化技术的探讨

OSPF对网络变化的适应性强,便于网络维护,但对设备的系统开销较大,不利于园区网低端设备运行。该文研究表明,可以利用区域划分、路由汇总、末节区域设置和重发布列表等OSPF技术过滤不必要的LSA,简化路由表,使该OSPF路由环境适合低端三层交换机运行,从而构建出一个稳定可靠、又方便管理的园区网。     

基于LSA的蔬菜短信自助交易系统的实现

基于LsA技术（关键语义提取技术）是一种信息检索代数模型,用统计的方法对大量文本集进行分析,该系统是基于LsA理论自主研发的蔬菜智能语义分析引擎的自助销售系统,采用J2EE三层架构的系统搭建,以UI／BL／DB层为分层原则,应用hibernate等主流开发框架,结合农业蔬菜销售的特点,构建一套适合农业蔬菜销售、信息收集、灵活查询的智能问答型语义搜索分析系统。     

OSPF协议Type 5 LSA的Forwarding Address属性讨论

主要讨论了OSPF的TYPE 5 LSA的Forward ing address属性有什么作用、如何填写、对计算TYPE 5 LSA的路由的影响,以及Forward ing address取值对OSPF的LSA 5路由成环是否关联,加深对OSPF协议的理解。     

Analyzing the discriminative attributes of products using text mining focused on cosmetic reviews

Consumers evaluate products through online reviews, in addition to sharing their product experiences. Online reviews affect product marketing, and companies use online reviews to investigate consumer attitudes and perceptions of their products. However, when analyzing a review, it is often the case that specific contexts are not taken into consideration and meaningful information is not obtained from the analysis results. This study suggests a methodology for analyzing reviews in the context of comparing two competing products. In addition, by analyzing the discriminative attributes of competing products, we were able to derive more specific information than an overall product analysis. Analyzing the discriminative attributes in the context of comparing competing products provides clarity on analyzing the strengths and weaknesses of competitive products and provides realistic information that can help the company's management activities. Considering this purpose, this study collected a review of the BB Cream product line in the cosmetics field. The analysis was sequentially carried out in three stages. First, we extracted words that represent discriminative attributes by analyzing the percentage difference of words. Second, different attribute words were classified according to the meaning used in the review by using latent semantic analysis. Finally, the polarity of discriminative attribute words was analyzed using Labeled-LDA. This analysis method can be used as a market research method as it can extract more information than a traditional survey or interview method, and can save cost and time through the automation of the program.     

Using big data analytics to study brand authenticity sentiments: The case of Starbucks on Twitter

There is a strong interest among academics and practitioners in studying branding issues in the big data era. In this article, we examine the sentiments toward a brand, via brand authenticity, to identify the reasons for positive or negative sentiments on social media. Moreover, in order to increase precision, we investigate sentiment polarity on a five-point scale. From a database containing 2,282,912 English tweets with the keyword ‘Starbucks’, we use a set of 2204 coded tweets both for analyzing brand authenticity and sentiment polarity. First, we examine the tweets qualitatively to gain insights about brand authenticity sentiments. Then we analyze the data quantitatively to establish a framework in which we predict both the brand authenticity dimensions and their sentiment polarity. Through three qualitative studies, we discuss several tweets from the dataset that can be classified under the quality commitment, heritage, uniqueness, and symbolism categories. Using latent semantic analysis (LSA), we extract the common words in each category. We verify the robustness of previous findings with an in-lab experiment. Results from the support vector machine (SVM), as the quantitative research method, illustrate the effectiveness of the proposed procedure of brand authenticity sentiment analysis. It shows high accuracy for both the brand authenticity dimensions’ predictions and their sentiment polarity. We then discuss the theoretical and managerial implications of the studies.     

一个OSPF实验模型的研究

动态路由协议OSPF是网络工程中使用很广泛的一种内部网关协议,由于其知识点比较多,配置比较复杂,在职业技术学院网络相关课程的教学中,往往无法对OSPF进行很详尽的讲授。本文旨在设计一种OSPF的实验模型,使职业技术学院的学生可以在课堂上或实验室里,模拟工程中实际环境,展开虚拟实训,从而掌握OSPF大部分技术点,并完成其关键配置,为其今后走向工怍岗位,提供更好的知识背景。