Automatic image semantic interpretation using social action and tagging data

The plethora of social actions and annotations (tags, comments, ratings) from online media sharing Websites and collaborative games have induced a paradigm shift in the research on image semantic interpretation. Social inputs with their added context represent a strong substitute for expert annotations. Novel algorithms have been designed to fuse visual features with noisy social labels and behavioral signals. In this survey, we review nearly 200 representative papers to identify the current trends, challenges as well as opportunities presented by social inputs for research on image semantics. Our study builds on an interdisciplinary confluence of insights from image processing, data mining, human computer interaction, and sociology to describe the folksonomic features of users, annotations and images. Applications are categorized into four types: concept semantics, person identification, location semantics and event semantics. The survey concludes with a summary of principle research directions for the present and the future.     

Supporting aspect orientation in business process management

Coping with complexity is an important issue in both research and industry. One strategy to deal with complexity is separation of concerns, which can be addressed using aspect-oriented paradigm. Despite being well researched in programming, this paradigm is still in a preliminary stage in the area of business process management (BPM). While some efforts have been made to introduce aspect orientation in business process modelling, there is no holistic approach with a formal underlying foundation to support aspect-oriented business process design and enactment, and this gap restricts aspect-oriented paradigm from being practically deployed in the area of BPM. Therefore, this paper proposes a sound systematic approach which builds on a formal syntax for modelling aspect-oriented business processes and a Petri Net-based operational semantics for enacting these processes. The approach enables the implementation of software system artefacts as a proof of concept to support design and enactment of aspect-oriented business processes in practice. The approach is demonstrated using a banking case study, where processes are modelled using a concrete notation that conforms to the proposed formal syntax and then executed in a state-of-the-art BPM system where the implemented artefacts are deployed.     

基于语义和多agent的电子政务协同工作模型研究

从电子政务的发展趋势出发,在语义网技术的基础上,采用XML/RDF描述协同过程中的语义信息;提出了任务—本体相关联的思想,采用RM-SFCA算法,动态生成全局本体,形成部门本体—全局本体的双本体层,用于构建语义约束。在上述基础上,结合多agent技术构建了基于语义和多agent的电子政务协同工作模型,以支持政务服务的协同工作,为建立一个虚拟的一站式服务平台奠定基础。     

Mining Semantic Trajectory Patterns from Geo-Tagged Data

User-generated social media data tagged with geographic information present messages of dynamic spatio-temporal trajectories. These increasing mobility data provide potential opportunities to enhance the understanding of human mobility behaviors. Several trajectory data mining approaches have been proposed to benefit from these rich datasets, but fail to incorporate aspatial semantics in mining. This study investigates mining frequent moving sequences of geographic entities with transit time from geo-tagged data. Different from previous analysis of geographic feature only trajectories, this work focuses on extracting patterns with rich context semantics. We extend raw geographic trajectories generated from geo-tagged data with rich context semantic annotations, use regions-of-interest as stops to represent interesting places, enrich them with multiple aspatial semantic annotations, and propose a semantic trajectory pattern mining algorithm that returns basic and multidimensional semantic trajectory patterns. Experimental results demonstrate that semantic trajectory patterns from our method present semantically meaningful patterns and display richer semantic knowledge.     

UML活动图描述工作流模型的执行语义

UML是软件工程中广泛应用的建模语言,但其主要问题是缺少严格的形式化语义,因而描述的模型容易产生歧义.根据UML活动图的语法和工作流系统的特点,为UML活动图定义了一种执行语义.基于时间转变系统模型,将工作流系统的执行描述为时间转变和数据转变两个交替进行的过程.时间转变描述时间的前进,数据转变修改工作流案例的状态,这种语义比层次状态图具有更强的描述并行的能力,比Petri网和进程代数更适合描述工作流模型.     

跨数据集评估的高光谱图像分类

目的 随着高光谱成像技术的飞速发展,高光谱数据的应用越来越广泛,各场景高光谱图像的应用对高精度详细标注的需求也越来越旺盛。现有高光谱分类模型的发展大多集中于有监督学习,大多数方法都在单个高光谱数据立方中进行训练和评估。由于不同高光谱数据采集场景不同且地物类别不一致,已训练好的模型并不能直接迁移至新的数据集得到可靠标注,这也限制了高光谱图像分类模型的进一步发展。本文提出跨数据集对高光谱分类模型进行训练和评估的模式。方法 受零样本学习的启发,本文引入高光谱类别标签的语义信息,拟通过将不同数据集的原始数据及标签信息分别映射至同一特征空间以建立已知类别和未知类别的关联,再通过将训练数据集的两部分特征映射至统一的嵌入空间学习高光谱图像视觉特征和类别标签语义特征的对应关系,即可将该对应关系应用于测试数据集进行标签推理。结果 实验在一对同传感器采集的数据集上完成,比较分析了语义—视觉特征映射和视觉—语义特征映射方向,对比了5种基于零样本学习的特征映射方法,在高光谱图像分类任务中实现了对分类模型在不同数据集上的训练和评估。结论 实验结果表明,本文提出的基于零样本学习的高光谱分类模型可以实现跨数据集对分类模型进行训练和评估,在高光谱图像分类任务中具有一定的发展潜力。     

旅游自动应答语义模型分析与实践

针对常见问答系统采用的以词法分析为基础的浅层语义模型难以有效挖掘用户问句深层语义的问题,本文立足于旅游问答应用领域,采用组合范畴语法对旅游问句进行句法分析,使用Lambda演算式表示问句语义,以此构建旅游领域问句的语义模型,以便于通过精确的问句语义快速查找应答结果.研究首先进行旅游领域数据采集与语料标注的准备性工作,并针对语料对旅游问句的句式句法进行分析;然后采用基于概率的组合范畴语法的监督学习过程,通过训练获得较为可靠的旅游问句语义词典;最后根据语义词典及其他相关知识,学习用户问句语义,构建旅游自动应答语义分析系统,着重于问句解析和相应的语义模型的构建.通过在评测集上的验证,这种语义解析方法在解析效果上有比较明确的提升.     

PAU: PARSING AND UNDERSTANDING WITH UNIFORM SYNTACTIC, SEMANTIC, AND IDIOMATIC REPRESENTATIONS

PAU is an all-paths chart-based unification parser that uses the same uniform representation for regular syntax, irregular syntax such as idioms, and semantics. PAU's representation has very little redundancy, simplifying the task of adding new semantics and syntax fo PAU's knowledge base. PAU uses relations between the syntax and semantics to avoid the proliferation of rules found in semantic grammars. By encoding semantics at the same level of representation as syntax, PAU is able to use semantic constraints early in the parse to eliminate semantically anomalous syntactic interpretations. Examples are given to show how PAU can handle the many eccentricities of different idioms using the same mechanisms as are used to handle regular syntax and semantics. These include the ability of some idioms, but not other idioms of the same syntactic form to undergo passivization, particle movement, action nominalization, indirect object movement, modification by adjectives, gerundive nominalization, prepositional phrase preposing, and topicalization. PAU's representation is bidirectional and is also used by a companion generator. PAU is designed to be efficient, runs in real time on typical workstations, and is being used in a number of natural language systems.     

Semantic information and knowledge integration through argumentative reasoning to support intelligent decision making

The availability of integrated, high quality information is a pre-requisite for a decision support system (DSS) to aid in the decision-making process. The introduction of semantic web ensures the seamless integration of information derived from diverse sources and transforms the DSS to an adoptable and flexible Semantic Web-DSS (Web-DSS). However, due to the monotonic nature of the layered development of semantic web, it lacks the capability to represent, reason and integrate incomplete and conflicting information. This, in turn, renders an enterprise incapable of knowledge integration; that is, integration of information about a subject that could potentially be incomplete, inconsistent and distributed among different Web-DSS within or across enterprises. In this article, we address the issues of incomplete and inconsistent semantic information and knowledge integration by using argumentation and argumentation schemes. We discuss the Argumentation-enabled Information Integration Web-DSS (Web@IDSS) along with its syntax and semantics for semantic information integration, and devise a methodology for sharing the results of Web@IDSS in Argument Interchange Format (AIF) format. We also discuss Argumentation-enabled Knowledge Integration Web-DSS (Web@KIDSS) for semantic knowledge integration. We provide formal syntax and semantics for the Web@KIDSS, propose a conceptual framework, and describe it in detail. We present the algorithms for knowledge integration and the prototype application for validation of results.     

Cyber-physical Systems as General Distributed Parameter Systems: Three Types of Fractional Order Models and Emerging Research Opportunities

Cyber-physical systems (CPSs) are man-made complex systems coupled with natural processes that, as a whole, should be described by distributed parameter systems (DPSs) in general forms. This paper presents three such general models for generalized DPSs that can be used to characterize complex CPSs. These three different types of fractional operators based DPS models are: fractional Laplacian operator, fractional power of operator or fractional derivative. This research investigation is motivated by many fractional order models describing natural, physical, and anomalous phenomena, such as sub-diffusion process or super-diffusion process. The relationships among these three different operators are explored and explained. Several potential future research opportunities are then articulated followed by some conclusions and remarks.      

An ontology‐based mechanism for automatic categorization of web services

The addition of semantic information into Web services (WS) results in more accurate search and retrieval in service registries. The key issue to facilitate organization of services, taking into account their semantics, is the development of automatic mechanisms that generate appropriate mappings between Web service elements and their semantics‐enabled counterparts. In this paper, we introduce an ontology‐based mechanism for automatic semantic categorization of WS and their structural components. The presented approach, as opposed to similar ones, takes into account the lexicographic, structural, and data type characteristics of WS. Moreover, a software tool that implements the proposed service categorization mechanism is presented, and a benchmark process is executed that reveals outstanding performance of the developed mechanism in comparison with a relevant state‐of‐the‐art approach. Copyright © 2011 John Wiley & Sons, Ltd.     

A feature-based syntax/semantics interface

Syntax/semantics interfaces using unification-based or feature-based formalisms are increasingly common in the existing computational linguistics literature. The primary reason for attempting to specify a syntax/semantics interface in feature structures is that it harmonizes so well with the way in which syntax is now normally described; this close harmony means that syntactic and semantic processing (and indeed other processing, see below) can be as tightly coupled as one wishes — indeed, there need not be any fundamental distinction between them at all. In this paper, we first point out several advantages of the unification-based view of the syntax/semantics interface over standard views. These include (i) a more flexible relation to nonsyntactic constraints on semantics, (ii) a characterization of semantic ambiguity, which in turn provides a framework in which to describe disambiguation, and (iii) the opportunity to underspecify meanings in a way difficult to reconcile with other views. The last point is illustrated with an application to the notorious scope ambiguity problem.     

用蒙太格文法解决汉语语义悖论

蒙太格文法是处理语法、语义和语用的典型方法,尤其在语义学方面独树一帜。通过对一个汉语语义悖论的安全分析,来表明Montague文法对于汉语语义悖论的解决,乃至对于整个汉语语义学的研究都具有非常重要的价值。     

Data Services with uncertain and correlated semantics

Currently, a good portion of datasets on Internet are accessed through data services, where user’s queries are answered as a composition of multiple data services. Defining the semantics of data services is the first step towards automating their composition. An interesting approach to define the semantics of data services is by describing them as semantic views over a domain ontology. However, defining such semantic views cannot always be done with certainty, especially when the service’s returned data are too complex. In such case, a data service is associated with several possible semantic views. In addition, complex correlations may be present among these possible semantic views, mainly when data services encapsulate the same data sources. In this paper, we propose a probabilistic approach to model the semantic uncertainty of data services. Services along with their possible semantic views are represented in probabilistic service registry. The correlations among service semantics are modeled through a directed probabilistic graphical model (Bayesian network). Based on our modeling, we study the problem of compositing correlated data services to answer a user query, and propose an efficient method to compute the different possible compositions and their probabilities.     

基于GIS语义的遥感图像检索

语义图像检索为填补图像低层视觉特征和用户高层语义之间的鸿沟而产生,图像语义描述和提取是其关键。提出了一种基于G IS语义的遥感图像检索(G IS sem antics-based remote sensing im age retrieval,简称G ISSB IR)方法,主要涉及空间对象的语义表达和语义匹配两方面内容。利用面向对象G IS语义模型和概念语义网络共同表达空间对象的语义,设计了语义调解器处理用户与系统之间的语义不一致。通过对G IS原子查询结果进行布尔运算得到矢量查询结果,在此基础上得到与G IS数据具有统一坐标框架的遥感图像检索结果。实验结果表明G ISSB IR方法是有效的。     

一种支持异构数据库集成的定义说明语言

提出了一种数据集成中间件Mediator定义说明语言,该语言通过提供了一套抽象的语言成分组件,能支持从一个高度抽象的层次来表达复杂数据集成语义,有效解决异构数据源集成时面临的结构/语义异构冲突,并自动生成数据集成中间件Mediator。介绍数据集成定义说明语言（DISL）主要语言成分组件的语法/语义、构造生成Mediator的方法以及应用体系结构,并讨论DISL-Mediator的内部体系结构和它的静态/动态特性.     

Tool support for the rapid composition, analysis and implementation of reactive services

We present the integrated set of tools Arctis for the rapid development of reactive services. In our method, services are composed of collaborative building blocks that encapsulate behavioral patterns expressed as UML 2.0 collaborations and activities. Due to our underlying semantics in temporal logic, building blocks as well as their compositions can be transformed into formulas and model checked incrementally in order to guarantee that important system properties are kept. The process of model checking is fully automated. Error traces are presented to the users as easily understandable animations, so that no expertise in temporal logic is needed. In addition, the results of model checking are analyzed, so that in some cases automated diagnoses and fixes can be provided as well. The formal semantics also enables the correct, automatic synthesis of the activities to state machines which form the input of our code generators. Thus, the collaborative models can be fully automatically transformed into executable Java code. We present the development of a mobile treasure hunt system to exemplify the method and the tools.     

Notes and annotations as information resources in a social networking platform

Taking notes and annotations contributes in the learning process. Many platforms are developed as Computer Supported Collaborative Learning (CSCL) thanks to advancements in new technologies. A common limitation of these platforms is the restricted ability to share/retrieve notes and annotations (Su, Yang, Hwang, & Zhang, 2010a). This is because the annotations in these platforms are disconnected from the information system and they are only accessible in the annotation system. As a result, the annotations could not be indexed as any other information resources (e.g., a document). This means that the annotations are not accessible/visible like other resources. In this paper, we present an original semantic model in which notes and annotations are modeled as information resources. The semantic model is used within the MEMORAe web platform. Then we detail an experiment of collaborative learning made within a university course using the MEMORAe web platform. The feedback of this experiment shows us that students are satisfied with the use of the MEMORAe web platform for helping them to index and retrieve notes and annotations as any information resources.