属性文法中变元间的关系

本文从模式的语义、句法描述着眼,分析了一个属性文法的产生式变元间的几种关系,把 这些关系作为语义部分的内容,从而推广了属性文法,以推广后的属性文法为基础,引入控制 连接图作为主要的限制条件,提出一种"语义程序文法",并把标准模式与畸变模式之间的联系 用限制条件描述.最后利用变元间的关系,把模式的描述与知识的表达联系起来.     

属性文法的研究与应用

本文详细讨论了有关属性文法的基本概念,属性文法的两种分类方法,两种分类之间的关系及属性文法的判定问题。本文还讨论了如何用属性文法定义编译程序的遍体制说明及与指称语义的关系。最后讨论了属性文法在编译程序中的应用与属性计算器的程序处理。     

编译程序的范式结构及用属性文法进行编译程序设计(下)

4.用属性文法进行编译程序设计近些年属性文法得到广泛的发展与应用.用属性文法进行编译程序设计可以是工具的辅助设计,也可以是人工进行设计.我们在这里主要介绍程序员如何根据属性文法的定义进行编译程序设计,并假定读者对属性文法的基本概念已经清楚.4.1属性文法的分类及判定问题     

基于ER模型的数据库受限汉语查询界面RChiQL的文法分析系统研究

RChiQL是一个基于受限汉语的关系数据库查询语言界面的计算模型,其中文法分析占有重要地位。本文引入了一种新的文法GWERSC(Grammar with ER Semantic Characteristics , ER语义特征文法) ,设计了分析算法,其内嵌的ER语义特征有利于排除语法分析的歧义并可简化语义分析。     

利用多重依赖关系的增量属性计值方法

本文利用属性文法中各个属性之间的多重依赖关系,针对某一类属性文法提出了一种新的增量属性计值算法。它不仅空间开销少,而且在时间上可以被证明是最优的。更进一步,我们还将该算法推广到能适用于一般的属性文法。同时保持了时间最优性与空间复杂性的价不变。     

一种识别线划图形的方法

把模式识的统计方法和句法方法统一起来成为一种有效的方法,已经有过一些研究, 取得了进展.本文在作者用属性文法来统一两种方法的工作基础上,借鉴认知心理学关于记 忆和语言的一些论点,讨论了高维属性文法的句法和词意之间的折衷关系,对于线划图形,给 出句法、词义以及模块之间关系信息的距离度量,从而可以用最小距离准则来进行线划图形 (尤其是汉字)的识别.     

网络通信协议的属性文法规格说明

本文给出一个基于属性文法的网络通信协议的形式说明与自动生成的模型.首先引入了一个扩展的属性文法描述工具,讨论了用其描述协议的并行、同步、延时（时序）等特性的有关问题；然后研究了基于属性文法的网络通信协议自动生成环境及其核心算法——属性计算（即语义分析）算法.     

英文生成系统词汇结构与功能位的逻辑描述

随着人工智能(AI)各领域的不断发展,越来越需要以自然语言形式进行人机对话,使其更加面向用户,特别是机器翻译的再度兴起,使得自然语言处理(NLP)面临新的挑战。在近几年,国内外一些语法理论陆续产生,如:管辖与约束理论(Government Binding Theory),词汇功能文法(Lexical Funotional Grammar),功能合一文法(Functional Unification Grammar)和词汇语义驱动理论等,但是不管你是用哪一种方法,     

新型属性图文法反应式规约验证方法

属性图文法广泛应用在软件设计阶段建模和分析阶段。命题式时序逻辑（propositional temporal logic）无法直接表达建模实体包含随时间演化的关联属性反应式规约,提出一种可支持通用图文法转换系统中相应规约的验证方法,通过引入标记节点及属性,将包含相应关联属性的规约公式等价转换为命题式时序逻辑,从而可以间接支持该类型规约的验证。以流行的对象式属性图文法模型检测工具GROOVE为平台,结合启发案例,验证了所提出方法的有效性。     

基于ER模型和受限汉语的数据库中文查询语言研究

本文给出了一个基于ER模型和受限汉语的关系数据库汉语查询语言的计算模型RChiQL(Restrictive Chinese Query Language)及其实现方案,系统模拟人脑对语言处理的并行机制,将中文查询句的处理分为四个相互依存、相互交织的步骤(词的切分,文法分析,语义分析和SQL转换) ,其中引入了一种新的文法GWERSC(Grammar with ER Semantic Characteristics ,ER语义特征文法) ,其内嵌的ER模型语义既有利于语法分析又简化了语义分析,取得了很好的效果。     

The Displacement Calculus

If all dependent expressions were adjacent some variety of immediate constituent analysis would suffice for grammar, but syntactic and semantic mismatches are characteristic of natural language; indeed this is a, or the, central problem in grammar. Logical categorial grammar reduces grammar to logic: an expression is well-formed if and only if an associated sequent is a theorem of a categorial logic. The paradigmatic categorial logic is the Lambek calculus, but being a logic of concatenation the Lambek calculus can only capture discontinuous dependencies when they are peripheral. In this paper we present the displacement calculus, which is a logic of intercalation as well as concatenation and which subsumes the Lambek calculus. On the empirical side, we apply the new calculus to discontinuous idioms, quantification, VP ellipsis, medial extraction, pied-piping, appositive relativisation, parentheticals, gapping, comparative subdeletion, cross-serial dependencies, reflexivization, anaphora, dative alternation, and particle shift. On the technical side, we prove that the calculus enjoys Cut-elimination.     

基于Unsharp量子逻辑的自动机和文法理论

初步建立了具有某种分配律的扩展格序效应代数和格序QMV代数这两种unsharp量子结构上的自动机与文法理论的基本框架。引入了ε-值正则文法的概念,证明了任意ε-值自动机识别的语言等价于某种ε-值正则文法所生成的语言;反之,任意[ε]-值正则文法所生成的语言等价于某种ε-值自动机识别的语言。讨论了ε-值正则语言在和、连接及反转运算下的封闭性质。     

Parsing and translation of (attributed) expansive graph languages for scene analysis

In this paper, we suggest a class of (attributed) expansive graph grammars which generate languages contained in a graph family ?. It turns out that by means of node renumbering using a very effi-cient algorithm, any graph in ? can be converted into a standard form, which enables the use of related string representation for that graph to facilitate the syntax analysis. As a consequence, the syntax analysis of (attributed) expansive graph language is very efficient and almost like the parsing of tree languages. Furthermore, a syntax-directed transla-tion can be established for mapping one (attributed) expansive graph language to another. Finally, since many relational graphs for scene analysis can be considered as belonging to these graph languages, the proposed graph grammar model appears to be quite attractive from the application point of view.     

Relational-grammar-based generation in the JETS Japanese-English machine translation system

This paper describes the design and function of the English generation phase in JETS, a minimal transfer, Japanese-English machine translation system that is based on the linguistic framework of relational grammar. To facilitate the development of relational grammar generators, we have built a generator shell that provides a high-level relational grammar rule-writing language and is independent of both the natural language and the application. The implemented English generator (called GENIE) maps abstract canonical structures, representing the basic predicate-argument structures of sentences, into well-formed English sentences via a two-stage plan-and-execute design. The modularity inherent in the plan-and-execute design permits the development of a very general and stable deterministic execution grammar. Another major feature of the GENIE generator is that it iscategory-driven, i.e., planning rules and execution rules are distributed over a part-of-speech hierarchy (down to individual lexical items) and are invoked via an inheritance mechanism only if appropriate for the category being processed. Categorydriven processing facilitates the handling of exceptions. The use of a syntactic planner and category-driven processing together provide a great deal of flexibility without sacrificing determinism in the generation process.     

Rough grammar for efficient and fault-tolerant computing on adistributed system

A method that combines global load balancing with dynamic task scheduling on a multiprocessor machine is presented. This method does not require prior knowledge of the run times of tasks, and is based on a rough grammar representing distributed computation is presented. Production rules are dynamically constructed when a concurrent program is run. The set of the rough grammar production rules is updated and rolled in a pipeline fashion, together with codes of the processes. This pipeline fashion of rolling the jobs defines the global job balancing. The rough grammar uses any operators and metrics, not only concatenation, inside its production rules. Performance parameters for the combination of a global load balancing and decentralized dynamic task scheduling are derived and compared with those for a statically scheduled multiprocessor. Based on these parameters, the decentralized methodology is shown to attain a much higher performance level and a highly improved fault tolerance     

Grammars and relations

The potential benefits obtained when context-free grammars are used to define complex objects in the relational model are demonstrated. The grammar formalism facilitates relational queries on the hierarchical structure of these objects and promotes the use of grammar-based tools as front ends to relational database systems     

A group-select operation for relational algebra and implicationsfor database machine design

A group-select operation has been defined for relational algebra. This operation is found to be useful for efficiently reducing expressions of nonprocedural relational languages that permit natural quantifiers. Conceptually, the operation first partitions a relation into blocks of tuples that have the same value for an attribute or attribute concatenation. It then extracts each block for which a specified number of tuples meet a specified condition. The quantity of tuples for the operation is specified by means of a natural quantifier. Performance of the group-select operation will be poor with conventional file processing, making the operation more suitable for use with a database machine with an associative memory     

A new approach to automatic speech summarization

This paper proposes a new automatic speech summarization method. In this method, a set of words maximizing a summarization score is extracted from automatically transcribed speech. This extraction is performed according to a target compression ratio using a dynamic programming (DP) technique. The extracted set of words is then connected to build a summarization sentence. The summarization score consists of a word significance measure, a confidence measure, linguistic likelihood, and a word concatenation probability. The word concatenation score is determined by a dependency structure in the original speech given by stochastic dependency context free grammar (SDCFG). Japanese broadcast news speech transcribed using a large-vocabulary continuous-speech recognition (LVCSR) system is summarized using our proposed method and compared with manual summarization by human subjects. The manual summarization results are combined to build a word network. This word network is used to calculate the word accuracy of each automatic summarization result using the most similar word string in the network. Experimental results show that the proposed method effectively extracts relatively important information by removing redundant and irrelevant information.