浅谈消防稳压设施的设计

探讨了GB50974-2014《消防给水及消火栓系统技术规范》稳压泵压力及流量的设计计算,阐述了现行规范及图集对稳压设施的规定,及对规范条文的进一步理解。     

交互式机译系统IHSMTS的多策略翻译引擎

采用了多策略的翻译方式,融合了,和机助人译等思想,提高了自动构造译文的质量,并实现了良好的经验记IHSMTSRBMTEBMT忆和知识自动获取。同时,采用智能的人机交互技术,构建了一个机助翻译平台。文章介绍了的翻译处理原理和系统关键技术的实IHSMTS现方法。     

交互式译系统IHSMTS的多策略翻译引擎

IHSMTS采用了多策略的翻译方式，融合了RBMT，EBMT和机助人译等思想，提高了自动构造文的质量，并实现了良好的经验记忆和知识自动获取，同时，采用智能人的机交互技术，构建了一个机组翻译平台，文章介绍了IHSMTS的翻译处理原理和系统关键技术的实现方法。     

多策略机器翻译系统IHSMTS中模式库的设计

本文介绍了语料库研究的一些特点，并以交互式多策略的思想为背景，对IHSMTS系统CBMT翻译引擎中模式库的设计思想，并对模式的表示，模式库的组织进行了阐述，方便了模式库检索，添加等操作的实现。同时介绍了近似模式匹配算法，从句法功能相似的角度抽取出所比较事例的功能词和句法特征，作为检索模式库和相似度计算的依据。最后介绍了模式库知识获取和知识精练的过程。     

Effective and Efficient Multi-Facet Web Image Annotation

The vast amount of images available on the Web request for an effective and efficient search service to help users find relevant images.The prevalent way is to provide a keyword interface for users to submit queries.However,the amount of images without any tags or annotations are beyond the reach of manual efforts.To overcome this,automatic image annotation techniques emerge,which are generally a process of selecting a suitable set of tags for a given image without user intervention.However,there are three main challenges with respect to Web-scale image annotation:scalability,noiseresistance and diversity.Scalability has a twofold meaning:first an automatic image annotation system should be scalable with respect to billions of images on the Web;second it should be able to automatically identify several relevant tags among a huge tag set for a given image within seconds or even faster.Noise-resistance means that the system should be robust enough against typos and ambiguous terms used in tags.Diversity represents that image content may include both scenes and objects,which are further described by multiple different image features constituting different facets in annotation.In this paper,we propose a unified framework to tackle the above three challenges for automatic Web image annotation.It mainly involves two components:tag candidate retrieval and multi-facet annotation.In the former content-based indexing and concept-based codebook are leveraged to solve scalability and noise-resistance issues.In the latter the joint feature map has been designed to describe different facets of tags in annotations and the relations between these facets.Tag graph is adopted to represent tags in the entire annotation and the structured learning technique is employed to construct a learning model on top of the tag graph based on the generated joint feature map.Millions of images from Flickr are used in our evaluation.Experimental results show that we have achieved 33% performance improvements compared with those single facet approaches in terms of three metrics:precision,recall and F1 score.     

基于语义相似度并运用语言学知识进行双语语句词对齐

一、引言自八十年代以来,基于统计(Statistics-Based)和基于实例(Example-Based)方法的出现及其广泛应用给机器翻译的研究工作注入了新的活力,标志着机器翻译进入了一个新时期。这两种方法共同的特点是:都需要一个双语语料库(Bilin-gual Corpora)直接或间接地作为翻译的知识库。这种双语语料库中包含了原文和译文相互对应的语言信息,是支持机器翻译的最为宝贵的资源。双语语料比单语种提供了更多的信息。在近些年里,在对篇章、段落、句子对齐进行了大量的研究之后,许多工作已经     

一种基于社会化标签的信息检索方法

社会化标签提供了网页信息的额外描述,直观上对搜索具有重要价值。该文提出一种新颖的利用社会化标签的分类属性进行检索的方法。该方法通过将群体的标注信息建模为高层类别来估计话题模型,然后基于该话题模型来对语言模型进行平滑。建模方法可以降低标注稀疏性的影响,有效地表达标签含义,从而提升检索效果。基于TREC评测构建的数据集上的实验结果表明,该方法优于基于LDA的检索方法以及现有其他基于标签数据的检索方法。