基于自然语言处理的计算机几何作图

如何将自然语言表述的初等几何命题自动转化为计算机可理解的作图语言是自然语言处理中的空白,也是实现教育软件人机交互的难点。文中通过对几何范围内的受限自然语言的研究,建立了有效可行的语言理解模型,实现了从自然语言到形式化规则的自动转化,并且设计出相应的软件。     

Formal syntax methods for natural language

This paper describes on-going research into the applications of some techniques normally used to formally specify and analyze the context-sensitive syntax of programming languages to the specification and analysis of the syntax of a natural language, namely English. The specific formal methods presently being investigated are two-level grammar (2LG) and the Vienna Definition Language (VDL). A preliminary subset of English has been established consisting of fifteen basic sentence patterns. 2LG and VDL specifications are given for one of these sentence types and the syntactic analysis of an English sentence using each of the two specifications is illustrated through an example.     

Automatic Generation of UML Class Diagrams for Object-oriented Design and Programing Course

UML Class diagram generation from textual requirements is an important task in object-oriented design and programing course. This study proposes a method for automatically generating class diagrams from Chinese textual requirements on the basis of Natural Language Processing (NLP) and mapping rules for sentence pattern matching. First, classes are identified through entity recognition rules and candidate class pruning rules using NLP from requirements. Second, class attributes and relationships between classes are extracted using mapping rules for sentence pattern matching on the basis of NLP. Third, we developed an assistant tool integrated into a precision micro classroom system for automatic generation of class diagram, to effectively assist the teaching of object-oriented design and programing course. Results are evaluated with precision, accuracy and recall from eight requirements of object-oriented design and programing course using truth values created by teachers. Our research should benefit beginners of object-oriented design and programing course, who may be students or software developers. It helps them to create correct domain models represented in the UML class diagram.     

Design,Implementation and Evaluation of an Inflectional Morphology Finite State Transducer for Irish

Minority languages must endeavour to keep up with and avail of language technology advances if they are to prosper in the modern world. Finite state technology is mature, stable and robust. It is scalable and has been applied successfully in many areas of linguistic processing, notably in phonology, morphology and syntax. In this paper, the design, implementation and evaluation of a morphological analyser and generator for Irish using finite state transducers is described. In order to produce a high-quality linguistic resource for NLP applications, a complete set of inflectional morphological rules for Irish is handcrafted, as is the initial test lexicon. The lexicon is then further populated semi-automatically using both electronic and printed lexical resources. Currently we achieve coverage of 89% on unrestricted text. Finally we discuss a number of methodological issues in the design of NLP resources for minority languages.     

基于概念特征的汉语交互类言说动词语义分析及同义词群的建构

人工智能的最重要内容之一是自然语言处理,建设词汇语义知识库是语言信息处理技术取得进步的重要保障。目前国内外基于同义词群(Synset)的词网研究存在结构不甚严谨,语义颗粒度不够精细,应用范围比较有限的问题。以“词群—词位”变体理论为基础建立多维特征概念语义网(Multi-D WordNet)是对这些问题进行解决的有效尝试,通过分析与描写基本词位(概念本体)与变体之间、变体与变体之间的关系,找出概念属性的差异,从而构建颗粒度更为精细的同义词群。言说动词的次范畴类“交互类”动词可作为研究个案,初步用来探讨这类典型词的语义结构及词群系统的建构规律。     

知识感知的预训练语言模型综述

随着自然语言处理（NLP）领域中预训练技术的快速发展,将外部知识引入到预训练语言模型的知识驱动方法在NLP任务中表现优异,知识表示学习和预训练技术为知识融合的预训练方法提供了理论依据。概述目前经典预训练方法的相关研究成果,分析在新兴预训练技术支持下具有代表性的知识感知的预训练语言模型,分别介绍引入不同外部知识的预训练语言模型,并结合相关实验数据评估知识感知的预训练语言模型在NLP各个下游任务中的性能表现。在此基础上,分析当前预训练语言模型发展过程中所面临的问题和挑战,并对领域发展前景进行展望。     

New perspectives in ontological analysis: Guidelines and rules for incorporating modelling languages into UEML

Ontological analysis of modelling languages has been mainly used for evaluating quality of modelling language w.r.t. one specific upper ontology. Generally speaking this evaluation has been done by identifying the coverage of the modelling language constructs w.r.t. the ontology and vice-versa. However, a quite limited support has been developed for performing the ontological analysis task. Specifically, various ontologies used for ontological analysis are not associated to a machine readable format; the coverage of modelling language constructs is mostly provided by informal tables mapping one construct on to one ontological concept; the way in which this coverage task is undertaken is poorly specified (resulting in distinct results for distinct experts involved), and finally, preventing any ontology enrichment for dealing with some specialised language constructs. This limited support also prevents application of ontological analysis outcomes to problems and domains dealing with interoperability, integration and integrated usage of enterprise and IS models, which is today one of the key aspects for making interoperable, maintainable and evolvable inter and intra enterprise software systems. The paper provides an overview of the Unified Enterprise Modelling Language (UEML) approach, which introduces advanced support to ontological analysis of modelling languages. The paper is specifically focused on the task of ontological analysis of modelling languages (named incorporation of modelling languages) by introducing and explaining several guidelines and rules for driving the task: therefore, not all the aspects of the UEML approach will be discussed through the paper. The guidelines and rules are illustrated by incorporation of three selected modelling constructs from IDEF3, a well known language for specifying enterprise processes.     

A frame-based approach for capturing semantics from Arabic text for text-to-sign language MT

This paper describes the design and implementation of a computational model for Arabic natural language semantics, a semantic parser for capturing the deep semantic representation of Arabic text. The parser represents a major part of an Interlingua-based machine translation system for translating Arabic text into Sign Language. The parser follows a frame-based analysis to capture the overall meaning of Arabic text into a formal representation suitable for NLP applications that need for deep semantics representation, such as language generation and machine translation. We will show the representational power of this theory for the semantic analysis of texts in Arabic, a language which differs substantially from English in several ways. We will also show that the integration of WordNet and FrameNet in a single unified knowledge resource can improve disambiguation accuracy. Furthermore, we will propose a rule based algorithm to generate an equivalent Arabic FrameNet, using a lexical resource alignment of FrameNet1.3 LUs and WordNet3.0 synsets for English Language. A pilot study of motion and location verbs was carried out in order to test our system. Our corpus is made up of more than 2000 Arabic sentences in the domain of motion events collected from Algerian first level educational Arabic books and other relevant Arabic corpora.     

信息抽取研究综述

信息抽取研究旨在为人们提供更有力的信息获取工具,以应对信息爆炸带来的严重挑战。与信息检索不同,信息抽取直接从自然语言文本中抽取事实信息。过去十多年来,信息抽取逐步发展成为自然语言处理领域的一个重要分支,其独特的发展轨迹———通过系统化、大规模的定量评测推动研究向前发展,以及某些成功启示,如部分分析技术的有效性、快速NLP系统开发的必要性,都极大地推动了自然语言处理研究的发展,促进了NLP研究与应用的紧密结合。回顾信息抽取研究的历史,总结信息抽取研究的现状,将有助于这方面研究工作向前发展。     

Natural language processing for Nepali text: a review

Because of the proliferation of Nepali textual documents online, researchers in Nepal and overseas have started working towards its automated analysis for quick inferences, using different machine learning (ML) algorithms, ranging from traditional ML-based algorithms to recent deep learning (DL)-based algorithms. However, researchers are still unaware about the recent trends of NLP research direction in the Nepali language. In this paper, we survey different natural language processing (NLP) research works with associated resources in Nepali language. Furthermore, we organize the NLP approaches, techniques, and application tasks used in the Nepali language processing using the comprehensive taxonomy for each of them. Finally, we discuss and analyze based on such assimilated information for further improvement in NLP research works in the Nepali language. Our thorough survey bestows the detailed backgrounds and motivations to researchers, which not only opens up new potential avenues but also ushers towards further progress of NLP research works in the Nepali language.

     

Clustering DTDs: An Interactive Two-Level Approach

XML（eXtensible Markup Language)is a standard which is widely applied in data representation and data exchange,However,as an important concept of XML,DTD(Document Type Definition)is not taken full advantage in current applications.In this paper,a new method for clustering DTDs is presented.and it can be used in XML document clustering.The two-level method clusters the elements in DTDs and clusters DTDs separately.Element clustering forms the first level and provides element clusters,which are the generalization of relevant elements.DTD clustering utilizes the generalized information and forms the second level in the whole clustering process.The two-level method has the following advantages:1) It takes into consideration both the content and the structure within DTDs;2) The generalized information about elements is more useful than the separated words in the vector model;3) The two-level method facilitates the searching of outliers.The experiments show that this method is able to categorize the relevant DTDs effectively.     

Natural language processing: a prolog perspective

Natural language processing (NLP) is a vibrant field of interdisciplinary Computer Science research. Ultimately, NLP seeks to build intelligence into software so that software will be able to process a natural language as skillfully and artfully as humans. Prolog, a general purpose logic programming language, has been used extensively to develop NLP applications or components thereof. This report is concerned with introducing the interested reader to the broad field of NLP with respect to NLP applications that are built in Prolog or from Prolog components.     

Parsing Turkish using the lexical functional grammar formalism

This paper describes our work on parsing Turkish using thelexical-functional grammar formalism [11]. This work represents the first effort for wide-coverage syntactic parsing of Turkish. Our implementation is based on Tomita's parser developed at Carnegie Mellon University Center for Machine Translation. The grammar covers a substantial subset of Turkish including structurally simple and complex sentences, and deals with a reasonable amount of word order freeness. The complex agglutinative morphology of Turkish lexical structures is handled using a separate two-level morphological analyzer, which has been incorporated into the syntactic parser. After a discussion of the key relevant issues regarding Turkish grammar, we discuss aspects of our system and present results from our implementation. Our initial results suggest that our system can parse about 82% of the sentences directly and almost all the remaining with very minor pre-editing.This work was done as a part of the first author's M.Sc. degree work at the Department of Computer Engineering and Information Science, Bilkent University, Ankara, 06533, Turkey.     

中文变体词的识别与规范化综述

网络书写具有随意性、非正规性等特点。变体词就是网络语言作为一种不规范语言的显著特色,人们往往出于避免审查、表达情感、讽刺、娱乐等需求将相对严肃、规范、敏感的词用相对不规范、不敏感的词来代替,用来代替原来词的新词就叫做变体词（Morph）。变体词和其对应的原来的词（目标实体词）会分别在非规范文本和规范文本中共存,甚至变体词会渗透到规范文本中。变体词使行文更加生动活泼,相关事件、消息也传播得更加广泛。但是因为变体词通常是某种隐喻,已不再是其表面字词的意义了,从而使网络上文体与正式文本（如新闻等）具有巨大的差异。由此如何识别出这些变体词及其所对应的目标实体词对于下游的自然语言处理技术具有重要的意义。本文首先介绍了变体词的定义和特征,变体词的生成规律,总结了当前变体词的识别和规范化的主要技术进展和成果,最后是此领域发展方向的展望。     

基于字符层马尔科夫模型的多语种识别

语种识别是机器翻译等多语种语言处理任务的必要预处理过程。但双字节编码语种的识别，如中文、日文等，尚未被充分研究和试验。本文采用Markov语言模型，提出并测试了一种有效的基于EM的训练算法。同时，给出了性能分析和与其他算法的比较。     

一种基于DSL的服务组合语言

针对大规模并发应用在组合服务中的服务调度问题,设计一种基于领域专用语言的服务组合语言,给出该语言的主要功能、构造过程和语言执行引擎的详细设计。该语言提供对Web服务组合过程的语义和语法描述,采用自顶向下的组合方式,能解决Web服务组合过程中的组合粒度控制和异构消息匹配等问题。