Story Parsing Grammar

Story understanding is one of the important branches of natural language understanding research in AI techniques.A new approach to story understanding is proposed in this paper.The so-called Story Parsing Grammar (SPG) is used to represent the story abstracting processes with different degrees in story understanding,and the story understanding process is converted to the storyn recognizing process done by the syntactic parser of SPG.This kind of story understanding is called story parsing.In this paper,firstly,a survey of story understanding research is given.Secondly,by the classification of various kinds of story structures,the so-called Case Frame Forest (CFF) is proposed to represent the superficial meaning of story.Based on CFF,a high-dimen-sional grammar,called Forest Grammar (FG),is defined.Furthermore,SPG is defined as a subclass of context-sensitive FG.Considering the context-sensitivity of story content,a type of context-sensitive derivation is defined in the definition of SPG.Lastly,data about runtime efficiency of the syntactic parsing algorithm of weak precedence SPG,a subclass of SPG,are given and analysed.     

含无序产生式的故事分析文法的研究

基于故事分析文法的故事理解法是本文作者在其博士论文中提出的一种面向故事深层含义的对语法、语义和语用综合进行理解的形式化方法，故事分析文法是一种高维的上下文有关文法，为了提高它的描述能力和表达范围，本文定义了一种特殊的产生式：无序产生式，并将它引入故事分析文法，讨论了由此带来的对故事分析文法的影响和无序产生式在故事分析文法中的性质，最后给出了含无序产生式的故事分析文法的一个子类文法的语法分析算法．     

话题关联识别中报道信息的动态扩充研究

话题关联识别用于判断新闻报道对流中每对中的两篇报道是否描述了同一个话题.为解决其中报道篇幅短小、稀疏问题严重及其内容存在漂移等问题,提出了一种动态信息扩充技术,用于改进报道表示模型.该技术用过去最新的话题相关报道来扩充当前报道,动态更新原有模型.此外,还研究了扩充信息的精化问题,通过有选择地加重一些重要特征的权重来减小扩充过程中噪音带来的影响.该方法在TDT4中的中文语料上进行了实验,结果表明动态信息扩充技术能够较大幅度地改进话题关联识别的性能,对多种特征采取的精化技术也对性能改进产生了较大影响.     

基于图算法的二元组合文法分析

为解决二元组合文法(BCG)的算符优先计算分析中不能共享分析树空间的问题,并降低分析算法的空间花费以提高分析效率,提出了一种基于图算法的BCG分析方法。该方法以表格方式存储分析过程中产生的所有边,分析完成后根据边的跨度构造分析树,从而使边不再局限于某一特定分析树中,再根据BCG文法的特性实现分析过程中的剪枝。实验结果表明,该方法在花费的时间、产生边的数量和最终结果树的数量上都明显低于传统的图算法和基于算符优先的算法。     

Improving agile requirements: the Quality User Story framework and tool

User stories are a widely adopted requirements notation in agile development. Yet, user stories are too often poorly written in practice and exhibit inherent quality defects. Triggered by this observation, we propose the Quality User Story (QUS) framework, a set of 13 quality criteria that user story writers should strive to conform to. Based on QUS, we present the Automatic Quality User Story Artisan (AQUSA) software tool. Relying on natural language processing (NLP) techniques, AQUSA detects quality defects and suggest possible remedies. We describe the architecture of AQUSA, its implementation, and we report on an evaluation that analyzes 1023 user stories obtained from 18 software companies. Our tool does not yet reach the ambitious 100 % recall that Daniel Berry and colleagues require NLP tools for RE to achieve. However, we obtain promising results and we identify some improvements that will substantially improve recall and precision.     

基于动态共现的中文话题关联检测

话题关联检测是话题检测与跟踪的一项子任务,是判断随机抽取的两篇新闻报道是否讨论同一个话题的技术。受词语共现模型的启发,结合话题关联检测的特点,提出了词语间的动态同现关系,实现了基于动态共现关系的报道相似度计算方法;探讨了相似度计算方法在中文话题关联检测中的应用。通过实验可知,动态共现关系可以在一定程度上反映报道的语义信息,相似度计算方法很好地改善了中文话题关联检测系统的性能,取得了不错的效果。     

Collaboration and co-ordination in mature eXtreme programming teams

Mature eXtreme programming (XP) teams are highly collaborative and self-organising. In previous studies, we have observed that these teams rely on two apparently simple mechanisms of co-ordination and collaboration: story cards and the Wall. Story cards capture and embody the user stories which form the basis of implementation, while the Wall is a physical space used to organise and display the cards being implemented during the current development cycle (called an iteration). In this paper, we analyse the structure and use of story cards and the Wall in three mature XP teams, using a distributed cognition approach. The teams work in different commercial organisations developing different systems, yet we find significant similarities between their use of these two artefacts. Although simple, teams use the cards and the Wall in sophisticated ways to represent and communicate information that is vital to support their activities. We discuss the significance of the physical medium for the story cards and the Wall in an XP team and discuss the considerations that need to be taken into account for the design of technology to support the teams.     

人机协作的用户故事场景提取与迭代演进

敏捷软件开发中常用用户故事表达需求：用户故事讲述了具体的用户角色希望软件完成的功能.系统新版本的需求常常来自多个用户故事的整合.随着版本的迭代,不断会有新的用户故事出现.用户故事的迭代式管理和整合是敏捷开发成功的关键.为帮助开发者掌握项目的用户故事需求,提出人机协作的用户故事理解、整合和管理方法,支持需求的迭代更新.具体而言,提出用户故事元模型和带场景细粒度描述的用户故事表示,从故事描述、功能特征属性以及场景3个维度表达用户故事.便于开发者理解用户故事所表达的功能需求.提出基于元模型的用户故事理解,以及用户故事表达元素的自动提取方法.提出人机协同式用户故事整合方法,使用功能场景图辅助开发者确定用户故事间的关联关系.提出基于功能场景图的用户故事迭代更新方法.案例研究展示了方法的可行性.     

Persuasive narrative advertisement generator: A microenterprise service innovation perspective

In the era of the service economy, service innovation is a means to cope with fierce competition within a fast-changing industry. However, most microenterprises are at a competitive disadvantage in that they have limited resources and information for putting service innovation into their business practice. Owing to their inferior situation, microenterprises often do not think service innovation is related to them, nor do they have the bravery to engage their innovation endeavors. This paper presents a novel and automatic approach that can generate persuasive narrative advertisements in the form of customized motivation stories intended to encourage microenterprises to consider innovation just as the protagonist does in a story. This study adopts a three-act structure as the story framework and takes advantage of Story of Mind elements, service innovation types and microenterprise individual information as the story elements. Our approach and its information system uses Probabilistic Extended FSMs to model the story frameworks and the story elements. The approach proposed here has preliminary been justified through the observational and analytical evaluation method and is believed to shed light on the development of automated persuasive narrative communications for electronic services.     

基于语义域语言模型的中文话题关联检测

关联检测是话题检测与跟踪领域的基础性研究,其任务是检测任意新闻报道对是否论述同一话题.通过分析报道内容的结构关系和语义的分布规律,提出基于语义域语言模型的关联性检测方法,并在此基础上检验融入依存分析的语义描述策略对该模型性能的影响.实验采用TDT4中文语料进行评测,结果显示语义域语言模型显著改进了现有检测系统的性能,其最小DET代价降低了约3个百分点.     

基于关联词对动态抽取的报道关系检测技术研究

报道关系检测是判断随机选取的两个新闻报道是否讨论同一话题的技术.提出了一种基于关联词对动态抽取的报道关系检测方法.关联词对是指在同一篇报道中出现的满足一定关系约束的两个单词,而关系约束是指一组特征的集合.该方法认为两篇报道中出现的相同的关联词对越多,两篇报道的相似度越大.实验证明基于关联词对动态抽取的报道关系检测方法取得了非常好的效果,从而证实了所提方法的有效性.同时,实验还表明,关系约束对该方法的成功实施起着非常重要的作用.     

一种有效的概率上下文无关文法分析算法*

句法分析的研究是自然语言处理领域的一个重要组成部分。该提出并实现了一种有效的概率上下无关法ＳＣＦＧ（ｓｔｏｃｈａｓｔｉｃ ｃｏｎｔｅｘｔ－ｆｒｅｅ ｇｒａｍｍｅｒ）的分析算法。首先对原有的ＧＬＲ分析有加以改造，以便能够利用分析过程的控制结构来计算有关的概率；然后对分析过程中的每个状态增设了下标，以区分不同的归约路径。通过上述手段，成功地引入了状态的前向（Ｆｏｒｗａｒｄ）概率和内（Ｉｎｎｅｒ）     

层级分类概率句法分析

对已有的句法分析中引入知识的方法进行了归纳分析,认为多种句法分析方法都可被看作是基于特征标记的分类,然后分析了其中的欠分类和过分类问题.在此基础上,提出一种层级分类短语结构文法和一种层级分类概率句法分析方法(hierarchically classified probabilistic context-free grammar),并设计了一种通过对实例进行聚类来消除句法规则的分类歧义方法.还进一步将层级分类扩展到概率上下文相关句法分析方法,利用上下文相关性的层级分类来解决引入上下文相关时的数据稀疏性问题.通过上述一系列方法有效地克服了过分类与前分类之间的矛盾.     

The Use of Stories in User Experience Design

Stories capture the characteristics of the design space and audience that designers and engineers need to understand to build a complete and useful software experience. A story is a design communication tool that transcends the cultural divides of multidisciplinary teams and intertwines a technology with its user's goals. This article describes how stories are powerful tools in software design, defines the elements that make a compelling story, and presents the use of stories at IBM from the authors' experience. It also explores the benefits at each phase of the design process and how stories evolve throughout the design process.     

User story clustering in agile development: a framework and an empirical study

Agile development aims at rapidly developing software while embracing the continuous evolution of user requirements along the whole development process. User stories are the primary means of requirements collection and elicitation in the agile development. A project can involve a large amount of user stories, which should be clustered into different groups based on their functionality’s similarity for systematic requirements analysis, effective mapping to developed features, and efficient maintenance. Nevertheless, the current user story clustering is mainly conducted in a manual manner, which is time-consuming and subjective to human bias. In this paper, we propose a novel approach for clustering the user stories automatically on the basis of natural language processing. Specifically, the sentence patterns of each component in a user story are first analysed and determined such that the critical structure in the representative tasks can be automatically extracted based on the user story meta-model. The similarity of user stories is calculated, which can be used to generate the connected graph as the basis of automatic user story clustering. We evaluate the approach based on thirteen datasets, compared against ten baseline techniques. Experimental results show that our clustering approach has higher accuracy, recall rate and F1-score than these baselines. It is demonstrated that the proposed approach can significantly improve the efficacy of user story clustering and thus enhance the overall performance of agile development. The study also highlights promising research directions for more accurate requirements elicitation.     

基于句式结构的汉语图解析句法设计

梳理了汉语语法学界对“句式”这一术语的认识分歧;从中文信息处理角度分析了当前本领域句法分析和树库构建缺乏句式结构的现状;对黎氏语法形式化研究作了一个最新的综述,指出其在句式结构方面的优势和仍存在的不足;以黎氏语法图解法为原型改造设计出一种新型的汉语图解析句法,具体包括图形化的句法结构表示和结构化的XML存储格式。     

基于带约束语义文法的领域相关自然语言理解方法

开放域问答系统通常可以借助一些数据冗余方法来提高问答准确性,而对于缺乏大规模领域语料的领域相关问答系统来说,准确理解用户的意图成为这类系统的关键。该文首先定义了一种带约束语义文法,与本体等语义资源相结合,可以在词汇级、句法级、语义级对自然语言句子的解析过程进行约束,解决自然语言理解歧义问题;然后给出了一个高效的文法匹配算法,其首先依据定义的各种约束条件预先过滤一些规则,然后依据提出的匹配度计算模型对候选的规则进行排序,找到最佳匹配。为了验证方法的有效性,将方法应用到两个实际的应用领域的信息查询系统。实验结果表明,本系统提出的方法切实有效,系统理解准确率分别达到了82.4%和86.2%,MRR值分别达到了91.6%和93.5%。     

一种特殊的上下文无关文法及其语法分析

SAQ系统是一个进行软件规约获取、检验和复用的实验系统，其中以上下文无关文法表示的概念是规约的一部分.SAQ要求将概念的词法和句法定义结合在一个上下文无关文法中.如果用常规的上下文无关文法描述诸如程序设计语言和自然语言等一些复杂概念的语法，则需要把诸如空格和回车等没有实质意义的分隔符包含到语法中去(这种描述方法称为朴素表示法),使得语法描述很累赘.为此，作者设计了一种特殊的上下文无关文法,它把通常上下文无关文法定义中的非终极符集合和终极符集合进行细化.用这种文法可以相对简洁地描述程序语言和自然语言等复杂概     

一种可行的自动程序理解途径

自动程序理解是软件工程和人工智能的非常活跃的研究领域，本文提出了一种独立于程序设计语言，具有明显结构性和流图结构的中间表示ｐｌａｎ来表示程序代码，本文首次提出了应用图文法分析技术于自动程序理解的方法，并给出了基于人工智能技术来进行自动程序理解的模型。     

Collaborative storytelling experiences in social media: Influence of peer-assistance mechanisms

Collaborative storytelling activities in social media environments are generally developed in a linear way in which all participants collaborate on a shared story as it is passed from one to another in a relay form. Difficulties with this linear approach arise when collecting the contributions of participants in to a coherent story. This study proposes a hypermedia approach to enable students to integrate the episodes of others to develop different branches of stories. Since these linear and nonlinear approaches facilitate students in developing stories in quite a different manner, students’ perceptions of linear and hypermedia approaches differ in their collaboration mechanisms, which may in turn affect positive inter-dependence and ultimate success in the collaborative storytelling. The results of an empirical study show that the performance of students in the hypermedia group was superior to that of members the linear group insofar as perception of collaborative process, peer support, authorship, and collaborative result where concerned.