基于语义轨迹的视频事件探测

视频事件探测是视频内容自动理解领域的一个重要研究问题.在视频事件探测中,感兴趣对象的运动轨迹常被作为视频中探测事件的一种重要依据.目前基于轨迹的事件探测方法主要集中于根据轨迹几何特征进行视频事件探测,而忽略了与轨迹相关的语义信息.然而我们知道,轨迹的产生往往受到一些与轨迹相关联的语义信息的影响,如轨迹产生时的地理信息等.将轨迹相关联的语义信息整合到轨迹中可以使我们了解更多关于轨迹的信息.语义轨迹为我们提供了一个将语义信息与轨迹信息有效整合的方法.该文将语义轨迹应用到视频事件探测领域,提出了一个基于语义轨迹的视频事件探测方法.该方法将视频中抽取的感兴趣对象的原始轨迹转化为语义轨迹,并根据语义轨迹探测可能的视频事件.同时该方法还提供了一个描述语义轨迹特征以及对语义轨迹与轨迹特征进行匹配的方法.最后我们通过实验分析验证了基于语义轨迹的视频事件探测方法的有效性.     

多角度语义轨迹相似度计算模型

移动设备的发展使得轨迹数据可以记录更多有用的信息,比如签到信息、活动信息,构成了语义轨迹数据.快速有效的轨迹相似度计算会为分析问题带来巨大好处,已有学者对轨迹相似性及语义轨迹相似性做出研究,并提出了一些有效的方法.但是现有轨迹相似性计算方法无法应用于语义轨迹数据,而目前的语义轨迹相似性计算方法又在轨迹采样频率低的情况下效果不佳.因此在解决轨迹相似性计算对低采样频率敏感的基础上,结合了语义轨迹的附加访问地点信息,提出了一种新的轨迹相似性计算模型,叫作多角度语义轨迹(MAST)相似度计算.模型基于LSTM并且引入自注意力机制,学习到的轨迹表达为多个关注轨迹不同方面的低维向量,构成了一个矩阵,从而解决了单一向量无法准确表达轨迹的问题.这个矩阵不仅包含轨迹的空间信息,也包含语义信息,可用于计算语义轨迹相似度.提出的模型在两个现实语义轨迹数据集上进行实验,实验数据表明MAST的计算结果优于现有方法.     

基于空间语义轨迹的GPS航迹行为特征检测研究

针对GPS航海定位系统轨迹检测缺乏语义的特点,提出一种基于空间语义轨迹的GPS航迹行为特征检测方法。该方法使用OWL形式描述GPS航迹行为特征,构建本体行为特征库以及提取航迹行为之间的数据依赖关系,在此基础上运用启发式的搜索算法生成关于Stop序列集的语义轨迹。然后,通过基于语义描述ALC-Tableau的逻辑推理,将Stop实例集与行为特征库相匹配。最后,通过实验分析验证该方法的有效性。     

一种基于语义轨迹的事件规则学习算法

视频上的事件探测对于视频检索与语义理解是一个很重要的工作.视频中的轨迹不仅记录了物体的移动信息,也反映了物体移动的动机,并与事件的发生密切相关.主要探讨了如何从轨迹抽取事件.然而,基于内容的视频事件分析中,从视频中抽取的低层特征与高层的语义特征存在一定的鸿沟.因此,利用领域知识标记的兴趣区域,提出一种新的语义轨迹表示方法,从而将视频中得到的原始轨迹转化为语义轨迹.同时,使用物体与兴趣区域关系的正则表达式描述视频中的语义事件.基于归纳学习的事件规则学习算法显示了正则表达式比传统的一阶谓词上的合式公式更易于学习.利用学习得到的事件规则可以很好地用于视频中语义事件的探测.最后,实验表明了事件探测的有效性。     

基于语义匿名代理的轨迹隐私保护方法

位置服务中隐私保护非常重要,移动设备的不可靠性往往会泄露个人轨迹数据等秘密信息。基于此提出新的轨迹隐私保护方法——基于语义匿名代理SAP(Semantic Anonymity Proxy),从传统轨迹匿名时使用的中心匿名服务器可能不可信为突破口,取消使用中心匿名服务器,使用基于背景地图模型的语义匿名和代理请求的方法实现基于位置的服务。在基于真实与模拟数据的测试中,在同CloakP2P比较时显示了其在轨迹隐私保护的有效性和服务的优质性。     

基于用户轨迹及基站语义的城市活动模式可视分析

移动运营商搭建的基站能够记录智能终端的活动,蕴涵着用户的移动行为以及基站的语义信息.针对城市中基站语义以及活动模式难以获取的问题,提出一种基于用户轨迹的基站语义及城市活动模式可视分析方法.该方法首先根据终端用户的轨迹构建基站序列,接着采用文本分析中的词嵌入技术对基站语义信息进行提取,对城市中的手机用户进行聚类以发现其移动模式.为了帮助用户对结果进行探索和分析,设计了基于用户轨迹以及基站语义的城市活动模式可视分析系统,能够根据用户的轨迹特征、基站的地域特征、用户访问基站的时空特征,对手机用户的行为以及城市的活动模式进行发现和解释.基于真实数据的实验结果表明,在系统用户的迭代交互中该方法能够帮助系统用户有效地结合基站轨迹及其基站语义信息,对城市居民行为模式以及城市整体的活动模式进行探索.     

基于结构化操作语义的安全协议分析框架研究

操作语义模型是一种用来分析安全协议的新模型,它以操作语义学为基础,结合了多种协议分析模型的优点,能直接分析多个协议的组合问题.本文在对安全协议操作语义模型进行研究的基础上,构建了一个基于结构化操作语义的安全协议分析框架,给出了该框架中的协议规格,协议运行,威胁模型和安全性质等形式化定义.最后,以经典的Needham Schroeder Lowe 协议为例,用该分析框架分析了其机密性和认证性.     

基于语义扩展的构件描述模型

根据构件模型的研究现状,针对目前的构件描述模型缺乏语义描述的支持,在刻面分类模式的基础上,提出了基于语义扩展的构件描述模型,采用OWL本体语言对构件本体的知识框架做了描述,并将此构件模型应用于教学评估系统,构造出了基于语义的软件构件检索体系构架,实现了对领域构件进行语义查询的目的.通过实验证明,该模型提高了构件检索的查全率和查准率.     

一种结合神经网络和敏感位置语义的轨迹隐私保护方法

目前,现有的轨迹隐私保护工作大多数考虑的是敏感位置或敏感区域,未能考虑到敏感位置语义且未能精准的描述出位置语义的敏感程度.针对此问题,本文提出了一个TP-SLS(A trajectory privacy protection method combining neural networks and sensitive location semantics)方法.首先,提出了敏感度感知算法,用于量化位置语义敏感度,实现“原子化”保护.其次,为了构建用户的敏感移动场景,建立了一个包含时空信息和位置语义敏感度的四元组并使用差分隐私进行干扰.同时,使用深度神经网络预测轨迹.最后,由于预测的轨迹存在废数据,提出了基于强化学习的优化轨迹算法,用于提高数据质量,完成轨迹数据发布.实验结果表明,TP-SLS方法在隐私保护强度和数据可用性两个方面优于现有的方案.     

基于树形语义框架的神经语义解析方法

语义解析的目标是将自然语言表达映射为机器可理解的逻辑表达,该任务的关键挑战在于难以刻画自然语言中蕴含的组合语义.目前,结合深度神经网络模型的语义解析方法已经成为该领域的主流方法,该类方法通常采用编码器—解码器框架,通过设计树形结构的解码器或者在解码器中添加语法限制,从语法层面上提升逻辑表达生成的准确率.与现有的神经语义...     

PVS Embedding of cCSP Semantic Models and Their Relationship

This paper demonstrates an embedding of the semantic models of the cCSP process algebra in the general purpose theorem prover PVS. cCSP is a language designed to model long-running business transactions with constructs for orchestration of compensations. The cCSP process algebra terms are defined in PVS by using mutually recursive datatype. The trace and the operational semantics of the algebra are embedded in PVS. We show how these semantic embeddings are used to define and prove a relationship between the semantic models by using the powerful induction mechanism of PVS.     

神经网络与组合语义在文本相似度中的应用

为了更好地提高短文本语义相似度分析能力,提出了基于神经网络和组合语义的短文本语义相似度分析算法。利用神经网络构建词义表示模型,结合局部和全局上下文信息学习词语在实际语境下的表示;通过句法分析,得到文本的依存关系,并依此构建组合关系树,使用组合语义模型得到整个文本的语义表示;通过计算两个语义表示结果之间的相似性来计算文本的语义相似度。实验分析结果表明,该方法能够在一定程度上提高文本语义分析能力。     

进程创建的语义及等价性

针对一个基于共享变量的带有进程创建的命令式语言,用变迁系统描述了它的结构操作语义,并用扩展的状态变迁迹模型定义了它的指称语义,在该模型下,状态变迁被区分为两种不同形式,分别表示发生在原进程和被创建进程中的状态变迁,这样便可以定义适当的语义复合运算,在对命令的指称进行复合时根据变迁类型的不同对变迁迹进行串行或交错连接,恰当地反映了进程的并发运行受创建命令在程序中的相对位置的限制,最后证明了这两个语义     

基于自然语言计算模型的汉语理解系统

本文首先给出了一种自然语言计算模型,该模型把自然语言交流过程划分为三个层次:语言形式,表层语义和深层语义,从而将自然语言理解抽象为一个复合函数UP(s,k),依据这个模型,我们设计了一个汉语理解系统,这个系统具有良好的扩展性和可移植性,该系统采用汉语语义结构文法来分析汉语句子,把语法分析和语义分析有机地结合在一起,文中形式定义了词语的深层语义以及深层语义的基本运算,给出了分析器、理解器以及生成器的算法。     

基于Object-Z的XPath形式化语义

本文描述了XPath语言的形式化语义。一个统一的面向对象的语义视角用于建模所有XPath语言构造。语义的表示采用形式化规范语言Object-Z的符号系统。这种高度结构化的语义模型具有简洁、可组合性和可复用性的特点。     

A comparative study of two formal semantics of the SIGNAL language

SIGNAL is a part of the synchronous languages family, which are broadly used in the design of safety-critical real-time systems such as avionics, space systems, and nuclear power plants. There exist several semantics for SIGNAL, such as denotational semantics based on traces (called trace semantics), denotational semantics based on tags (called tagged model semantics), operational semantics presented by structural style through an inductive definition of the set of possible transitions, operational semantics defined by synchronous transition systems (STS), etc. However, there is little research about the equivalence between these semantics. In this work, we would like to prove the equivalence between the trace semantics and the tagged model semantics, to get a determined and precise semantics of the SIGNAL language. These two semantics have several different definitions respectively, we select appropriate ones and mechanize them in the Coq platform, the Coq expressions of the abstract syntax of SIGNAL and the two semantics domains, i.e., the trace model and the tagged model, are also given. The distance between these two semantics discourages a direct proof of equivalence. Instead, we transformthem to an intermediate model, which mixes the features of both the trace semantics and the tagged model semantics. Finally, we get a determined and precise semantics of SIGNAL.     

The semantics of the combination of atomized statements and parallel choice

In this paper we define a uniform language that is an extension of the language underlying the process algebraPA. One of the main extensions of this language overPA is given by so-called atomizing brackets. If we place these brackets around a statement then we treat this statement as an atomic action. Put differently, these brackets remove all interleaving points. We present a transition system for the language and derive its operational semantics. We show that there are several options for defining a transition system such that the resulting operational semantics is a conservative extension of the semantics forPA. We define a semantic domain and a denotational model for the language. Next we define a closure operator on the semantic domain and show how to use this closure operator to derive a fully abstract denotational semantics. Then the algebraic theory of the language is considered. We define a collection of axioms and a term rewrite system based on these axioms. Using this term rewrite system we are able to identify normal forms for the language. It is shown that these axioms capture the denotational equality. It follows that if two terms are provably equal then they have the same operational semantics. Finally, we show how to extend the axiomatization in order to axiomatize its operational equivalence.     

Trace Semantics and Algebraic Laws for Total Store Order Memory Model

Modern multiprocessors deploy a variety of weak memory models(WMMs).Total Store Order(TSO) is a widely-used weak memory model in SPARC implementations and x86 architecture.It omits the store-load constraint by allowing each core to employ a write buffer.In this paper,we apply Unifying Theories of Programming(abbreviated as UTP) in investigating the trace semantics for TSO,acting in the denotational semantics style.A trace is expressed as a sequence of snapshots,which records the changes in registers,write buffers and the shared memory.All the valid execution results containing reorderings can be described after kicking out those that do not satisfy program order and modification order.This paper also presents a set of algebraic laws for TSO.We study the concept of head normal form,and every program can be expressed in the head normal form of the guarded choice which is able to model the execution of a program with reorderings.Then the linearizability of the TSO model is supported.Furthermore,we consider the linking between trace semantics and algebraic semantics.The linking is achieved through deriving trace semantics from algebraic semantics,and the derivation strategy under the TSO model is provided.     

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.     

Ontology and rule-based natural language processing approach for interpreting textual regulations on underground utility infrastructure

The nation’s massive underground utility infrastructure must comply with a multitude of regulations. The regulatory compliance checking of underground utilities requires an objective and consistent interpretation of the regulations. However, utility regulations contain a variety of domain-specific terms and numerous spatial constraints regarding the location and clearance of underground utilities. It is challenging for the interpreters to understand both the domain and spatial semantics in utility regulations. To address the challenge, this paper adopts an ontology and rule-based Natural Language Processing (NLP) framework to automate the interpretation of utility regulations – the extraction of regulatory information and the subsequent transformation into logic clauses. Two new ontologies have been developed. The urban product ontology (UPO) is domain-specific to model domain concepts and capture domain semantics on top of heterogeneous terminologies in utility regulations. The spatial ontology (SO) consists of two layers of semantics – linguistic spatial expressions and formal spatial relations – for better understanding the spatial language in utility regulations. Pattern-matching rules defined on syntactic features (captured using common NLP techniques) and semantic features (captured using ontologies) were encoded for information extraction. The extracted information elements were then mapped to their semantic correspondences via ontologies and finally transformed into deontic logic (DL) clauses to achieve the semantic and logical formalization. The approach was tested on the spatial configuration-related requirements in utility accommodation policies. Results show it achieves a 98.2% precision and a 94.7% recall in information extraction, a 94.4% precision and a 90.1% recall in semantic formalization, and an 83% accuracy in logical formalization.