SEMANTIC ANALYSIS AND IN-DEPTH UNDERSTANDING OF TECHNICAL TEXTS

We explored the problem of achieving in-depth understanding of natural language sentences from narrative technical reports through knowledge-based free text understanding. We rely on the assumption that texts in an expert domain convey much implicit information, which can be recovered by building and reasoning on a model of the situation described with the help of both linguistic and detailed world knowledge. We describe a two-step approach to semantic analysis: the first step assembles a conceptual representation of a sentence and deals with linguistic issues; the second step actually builds and runs the situational model and is totally dedicated to representation and inference. We evaluated this approach by designing a research prototype that processes sentences from clinical narratives in a medical specialty. This prototype was fully implemented and was tested on actual sentences. We hereby give a detailed account of this implementation as well as the first results obtained.     

基于文本分析的知识获取系统设计与实现

知识获取一直以来都是构建专家系统的瓶颈问题.针对该问题,利用自然语言处理技术,设计并实现一个针对化学科技文献进行分析的知识获取系统,并对其关键技术进行分析.系统对输入文本进行分词及词性标注,在此基础上,使用Tregex在句法分析树上进行实体识别,同时利用依存关系进行搭配词识别.实验结果表明了该系统的有效性.     

基于潜在语义分析的文本连贯性分析

文本连贯性分析是计算机辅助评估中的重要内容,是对文本的表达质量进行评估的基础.提出一种将潜在语义分析方法与基于有序聚类的层次分析方法相结合的文本层次结构分析方法,该方法保证了层次划分的有序性,可操作性强,不依赖于具体领域.基本思想是:对于输入文本,首先识别文本物理结构,然后将文本依据主题划分为若干层次,最终获得文本的逻辑结构.实验结果表明,该方法是有效的,其准确率达到74.96%.     

USING A FUNCTIONAL LANGUAGE FOR PARSING AND SEMANTIC PROCESSING

This paper describes an original approach to semantics representation based on the use of a non-strict functional programming language with polymorphic typing. This approach provides a unified formalism needing no preprocessing or postprocessing to the functional language itself: parsing and semantics are declared naturally using function definition and evaluation is done by lambda application along the lines of Montague. We show that by changing only the model we can, after parsing, compute either the truth value of a sentence or its parse tree.     

潜在语义分析中词汇-文本矩阵奇异值分解的并行实现

针对潜在语义分析中词汇-文本矩阵奇异值分解的特点,设计并实现了一种基于单边Jacobi的矩阵奇异值分解的并行算法.并行算法采用了一种新的扫描策略和任务划分策略,该策略在一次扫描中能产生n(n-1)/2个不同的列向量对,同时能够对矩阵的列向量按模排序,使奇异值按从大到小的顺序排列.通过在自强3000高性能计算机上的实验表明,并行算法大大缩短了奇异值分解的计算时间,而且随着矩阵规模逐渐变大,加速比趋于稳定.     

一个基于语义分析的倾向性文档过滤系统

目前的过滤系统大都是基于关键词的,这类系统适用于主题性过滤,而对倾向性过滤效果不好。本文提出一种适用于倾向性文档过滤的系统,通过语义分析,有效地识别和过滤倾向性文本信息。     

Frame-based representation of philosophical systems using a knowledge engineering tool

This article addresses the methodological problem of the non-linear representation of philosophical systems in a computerized knowledge base. It is a problem of knowledge representation as defined in the field of artificial intelligence. Instead of a purely theoretical discussion of the issue, we present selected results of a practical experiment which has in itself some theoretical significance. We show how one can represent different philosophies using CODE, a knowledge engineering system developed by artificial intelligence researchers. The hypothesis is that such a computer based representation of philosophical systems can give insight into their conceptual structure. We argue that computer aided text analysis can apply knowledge representation tools and techniques developed in artificial intelligence and we estimate how philosophers as well as knowledge engineers could gain from this cross-fertilization. This paper should be considered as an experiment report on the use of knowledge representation techniques in computer aided text analysis. It is part of a much broader project on the representation of conceptual structures in an expert system. However, we intentionally avoided technical issues related to either Computer Science or History of Philosophy to focus on the benefit to enhance traditional humanistic studies with tools and methods developed in AI on the one hand and the need to develop more appropriate tools on the other. Gilbert Boss is professor of Philosophy at Université Laval, Québec. He is the author of several books, including Les machines à penser. L'homme et l'ordinateur,Zurich: Grand Midi, 1987, and John Stuart Mill. Induction et utilité,Paris: PUF, 1990. His main fields of research are modern philosophy, philosophy of culture, philosophical discourse and systems, artificial intelligence. Maryvonne Longeart is professor of Computer Science at UQAH, Hull, Québec. Her research interests include object oriented design methodologies and knowledge representation. She received a PhD in Philosophy from the University of Ottawa in 1978 and a BSc in computer science in 1987. She contributed to the Encyclopédie philosophique universelle,PUF, 1992 and published several papers on the representation of complex conceptual systems.Douglas Skuce is professor of computer science at the University of Ottawa. He has worked in the area of knowledge engineering since his PhD (McGill, 1977). During 1978-present he has been developing the CODE system for various applications, including terminology and software development. Currently, his interests include designing ontologies for knowledge exchange and coupling large corpora to systems such as CODE.     

基于显著性语义属性的交互式非标人像检索方法

针对现有各类非标人像检索存在的问题,进行深入、系统的分析研究,提出一种基于显著性语义属性的交互式非标人像检索方法.通过多标签分类神经网络,生成基于公安行业语义属性的人像表示集;根据人工定义的显著性属性,通过改进的融合相似度距离函数计算方法和快速缩小检索范围的分库权值排序策略实现快速收敛.所提方法通过层进式的交互检索方案...     

基于自然语言语义分析的Internet文件分类与过滤

网上文件过滤是网络信息安全研究的重要课题。传统的过滤方法简单地把关键字匹配作为分类的依据,常导致漏判误判等问题。文中提出一种基于自然语言理解的语义模板算法解决网上文件分类过滤的问题。实验结果表明该方法漏判误判率较低,是一种行之有效文件分类方法。     

语义图像检索研究进展

语义图像检索已成为解决图像简单视觉特征和用户检索丰富语义之间存在的“语义鸿沟”问题的关键。从图像语义描述方式、图像语义抽取方法和语义检索系统设计3个方面对语义图像检索的研究状况进行了分析和研究;讨论了面向对象的图像内容模型和图像语义表示问题;对利用系统知识的提取、根据用户交互的提取和利用外部信息源的语义生成等具有代表性的语义处理方法进行了阐述;介绍了系统设计中用户界面和语义处理的不同方式,最后从对象识别、语义抽取规则、用户检索模型和图像检索性能评价标准4个方面剖析了实现图像语义处理所面临的困难,并提出了一些初步解决思路。