Automated and flexible composition based on abstract services for a better adaptation to user intentions

In recent years, the composition of loosely coupled services with the aim of satisfying the user intention is a widely followed research topic. The composition of services implies the ability to select, coordinate, interact, and interoperate existing services. This is considered as a complex task. This complexity is mainly due to the large number of available services and their heterogeneity as they are created by different organizations. This complexity is increased when services must be dynamically and automatically composed to meet requirements which are not satisfied by existing services. In fact, an approach for service composition must offer the potential to achieve flexible and adaptable applications, by selecting and combining services based of the request and the context of the user. In this perspective, different approaches have been developed for services composition. However, most of the existing composition approaches tend to be static and not flexible in the sense that they do not have the ability to adapt to user requirements.To overcome these challenges, we propose a composition approach in which the generation of the composition schema is performed at runtime through the use of abstract services provided at design time. The composition process that we propose takes as input a structure of user requirements materialized by a graph of intentions and enriches this graph to explicit the implicit relationships. The enriched graph is used to generate an initial composition schema by building the control flow and selecting the appropriate abstract services. The selection of these services is based on the semantic matching and the degree of semantic affinity between abstract services. Then, the final composition schema is generated using a refinement mechanism of abstract services using semantic matching techniques and taking into account user context and constraints.     

本体驱动的语义Web服务动态复合的研究

传统Web服务的复合由于缺乏足够的语义信息而大大降低了服务复合的效率和准确率。语义Web弥补了传统Web语义不足的缺点。但是,面对语义Web上分布的海量知识,如何有效地利用语义信息实现Web服务复合成为一个迫切需要解决的问题。文章针对这一问题,提出一种基于多维用户模型的动态服务复合机制。该机制在Web服务语义标识的启发下通过语义匹配算法能够实现Web服务的顺序复合和并行复合。采用这种服务复合机制将会在一定程度上提高语义Web服务复合的效率和准确率。     

Discovering semantic associations among Web services based on the qualitative probabilistic network

In recent years, the intelligent management and decision of Web services have attracted more and more attention due to the wide applications in various aspects of the real world. With the increase of Web services in an organization, the desired on-line services should be located rapidly requiring not only the syntactic but also the semantic techniques. In addition, aiming at fulfilling complex applications by discovering and composing available services automatically and precisely, it is indispensable to develop an underlying model and the corresponding measure for semantic associations among given Web services. In this paper, by mining the historical invocations of component services, we first construct a semantic model to describe their behavior rules based on the qualitative probabilistic network. Further, we propose a distance measure and the approach to discovering semantic associations among Web services. Preliminary experiments and performance studies show that our methods are feasible. Moreover, high recall and precision can be achieved when our methods are applied to Web service search.     

Learning the semantics of structured data sources

Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data that can be leveraged to build and augment knowledge graphs. However, they rarely provide a semantic model to describe their contents. Semantic models of data sources represent the implicit meaning of the data by specifying the concepts and the relationships within the data. Such models are the key ingredients to automatically publish the data into knowledge graphs. Manually modeling the semantics of data sources requires significant effort and expertise, and although desirable, building these models automatically is a challenging problem. Most of the related work focuses on semantic annotation of the data fields (source attributes). However, constructing a semantic model that explicitly describes the relationships between the attributes in addition to their semantic types is critical.We present a novel approach that exploits the knowledge from a domain ontology and the semantic models of previously modeled sources to automatically learn a rich semantic model for a new source. This model represents the semantics of the new source in terms of the concepts and relationships defined by the domain ontology. Given some sample data from the new source, we leverage the knowledge in the domain ontology and the known semantic models to construct a weighted graph that represents the space of plausible semantic models for the new source. Then, we compute the top k candidate semantic models and suggest to the user a ranked list of the semantic models for the new source. The approach takes into account user corrections to learn more accurate semantic models on future data sources. Our evaluation shows that our method generates expressive semantic models for data sources and services with minimal user input. These precise models make it possible to automatically integrate the data across sources and provide rich support for source discovery and service composition. They also make it possible to automatically publish semantic data into knowledge graphs.     

Artemis: Deploying semantically enriched Web services in the healthcare domain

An essential element in defining the semantics of Web services is the domain knowledge. Medical informatics is one of the few domains to have considerable domain knowledge exposed through standards. These standards offer significant value in terms of expressing the semantics of Web services in the healthcare domain.In this paper, we describe the architecture of the Artemis project, which exploits ontologies based on the domain knowledge exposed by the healthcare information standards through standard bodies like HL7, CEN TC251, ISO TC215 and GEHR. We use these standards for two purposes: first to describe the Web service functionality semantics, that is, the meaning associated with what a Web service does and secondly to describe the meaning associated with the messages or documents exchanged through Web services.Artemis Web service architecture uses ontologies to describe semantics but it does not propose globally agreed ontologies; rather healthcare institutes reconcile their semantic differences through a mediator component. The mediator component uses ontologies based on prominent healthcare standards as references to facilitate semantic mediation among involved institutes. Mediators have a P2P communication architecture to provide scalability and to facilitate the discovery of other mediators.     

Compositional algebra for interactive data access

An important issue for the success of a database application is the effectiveness of its interface. Frequently a relevant part of the programming effort is devoted to the generation of interfaces. The visual programming environments reduce only partly this effort, and in particular, things become more complicated when data coming from different sources (different views in the same database or even views from different databases or systems) are to be related and must cooperate in the data navigation and manipulation task. To overcome this problem we present a new database access paradigm based on an algebra on the domain of computational abstractions called “services” which include both dimensions: the data access computation and the user interaction. This means that the interaction is not implemented by using separated constructs as happens for traditional computational models; on the contrary, as the interaction is an integral part of the service paradigm, the user interaction is computed starting from the declarative specification of the data access itself. The combination of services in a service expression through the operators defined by the service algebra makes it possible to generate cooperating user interfaces for complex data navigation and manipulation. Through algebraic properties, which hold both from the data and user interface point of view, the service expressions can be simplified and optimized guaranteeing their initial semantics. The paper shows the application of the service algebra to the relational environment by means of a simple extension to SQL. Finally, the paper describes a tool based on a three tier architecture and on Java technology for developing and distributing services in Web environment. Services and combination of services expressed with the service algebra are automatically translated into Java objects, allowing the rapid development of platform independent data access services.     

Composing semantic Web services under constraints

Web service composition is an inevitable aspect of Web services technology, which solves complex problems by combining available basic services and ordering them to best suit the problem requirements. Automatic composition gives us flexibility of selecting best candidate services at composition time satisfying QoS requirements; this would require the user to define constraints for selecting and composing candidate Web services. In this work, a Web service composition approach is presented in which a rich set of constraints can be defined on the composite service. The output of the framework is the schedule of Web service composition in which how and when services are executed is defined. The basic properties of the proposed approach is converting Web service composition problem into a constraint satisfaction problem in order to find the best solution that meets all criteria defined by user and providing semantic compatibility and composability during composition.     

Improving Ocean Data Services with Semantics and Quick Index

Massive ocean data acquired by various observing platforms and sensors poses new challenges to data mana-gement and utilization.Typically,it is difficult to find the desired data from the large amount of datasets efficiently and effectively.Most of existing methods for data discovery are based on the keyword retrieval or direct semantic reasoning,and they are either limited in data access rate or do not take the time cost into account.In this paper,we creatively design and implement a novel system to alleviate the problem by introducing semantics with ontologies,which is referred to as Data Ontology and List-Based Publishing (DOLP).Specifically,we mainly improve the ocean data services in the following three aspects.First,we propose a unified semantic model called OEDO (Ocean Environmental Data Ontology) to represent heterogeneous ocean data by metadata and to be published as data services.Second,we propose an optimized quick service query list (QSQL) data structure for storing the pre-inferred semantically related services,and reducing the service querying time.Third,we propose two algorithms for optimizing QSQL hierarchically and horizontally,respectively,which aim to extend the semantics relationships of the data service and improve the data access rate.Experimental results prove that DOLP outperforms the benchmark methods.First,our QSQL-based data discovery methods obtain a higher recall rate than the keyword-based method,and are faster than the traditional semantic method based on direct reasoning.Second,DOLP can handle more complex semantic relationships than the existing methods.     

OWL-S的形式语义

本文分析了目前语义Web服务的研究现状和存在的问题,特别是语义web服务描述本体OWL-S的形式语义研究中存在的问题,在Srini Narayanan等人研究的基础上,用情景演算理论进一步研完了OWL—S中组合服务描述的形式语义,从而完善了OWL—S的形式语义,为语义Web服务提供了合理的理论基础。     

基于高斯过程分类器的三维模型多粒度语义检索

为解决三维模型语义检索中用户检索意图不一致问题,建立多粒度语义检索框架,使学习模型能够有效地适应用户的不同检索意图。首先对模型分类知识进行层次划分,形成语义概念的多粒度结构。然后提取一种多视图特征来描述三维模型的形状特性,并采用高斯过程分类器建立不同粒度层次上的学习模型,实现低层特征和查询概念之间的语义一致性描述。和已有研究相比,多粒度语义检索框架使用户可通过语义粒度级别变化进行检索意图设置,从而检索结果尽可能符合用户语义。在实验部分,采用三维模型基准数据库对框架进行算法性能测试。结果表明,检索准确率要明显提高,并且符合人类思维特点。     

OntoPipeliner: An ontology-based automatic semantic service pipeline generator

The Web is a distributed environment rich with Web services going through continual metamorphosis; thus, sustaining semantic stability of service composition has become a major challenge. Automatic service composition – enabled both by the use of ontologies that describe service domains and by user-specified constraints bound to the ontologies – provides us candidate service pipelines at composition design time. The ontology-based languages for semantically describing web services, such as OWL-S, have been widely used. Though rich and comprehensive in their expressiveness, the use of these languages still leaves much of composition process manual. In this work, we present an ontology-based semantic web service composition system called OntoPipeliner. It employs a novel way of utilizing characteristics of Web services that reflect the classes and properties of domain ontologies and provides the ontology-guided constraints for automatic composition of services, in order to guide the user toward the best pipeline that meets the user requirements.     

一种用户需求驱动的服务资源建模方法

面向用户需求通过松散耦合的服务资源的重用和重组,实现其按需发现与组合,正成为网络化软件主流的开发范型。如何对服务进行建模已成为这种范型中的一个重要问题。提出一种用户需求驱动、基于RGPS(Role-Goal-Process-Service)领域资产的服务建模方法。通过对服务模型进行语义需求封装来满足用户需求,从而实现用户需求和服务之间的动态"握手"。该方法已在原型系统中得以应用和验证。     

iMashup: a mashup-based framework for service composition

The Web has undergone a tremendous change from a primarily publication platform towards a participatory and"programmable"platform,where a large number of heterogeneous Web-delivered services(including SOAP and RESTful Web services,RSS and Atom feeds)are emerging.It results in the creation of Web mashup applications with rich user experiences.However,the integration of Web-delivered services is still a challenging issue.It not only requires the developers’tedious eforts in understanding and coordinating heterogeneous service types,but also results in the time-consuming development of user interfaces.In this paper,we propose the iMashup composition framework to facilitate mashup development and deployment.We provide a unified mashup component model for the common representation of heterogeneous Web-delivered service interfaces.The component model specifies necessary properties and behaviors at both business and user interface level.We associate the component model with semantically meaningful tags,so that mashup developers can fast understand the service capabilities.The mashup developers can search and put the proper mashup components into the Web browser based composition environment,and connect them by data flows based on the tag-based semantics.Such an integration manner might prevent some low-level programming eforts and improve the composition efciency.A series of experimental study are conducted to evaluate our framework.     

基于功能属性语义的Web服务组合方法

Web服务组合方法是Web服务研究领域的热点之一,常用的方法是通过Web服务的input和output参数的匹配,将已有的Web服务组合成满足用户复杂需求的Web服务。但普遍存在缺乏对Web服务功能属性语义的考虑,而且因为随着Web服务的数量上的急剧增长,如果对每一种可能的组合都进行考虑则会增加组合服务的复杂度。为此提出一种基于Web服务语义图模型的服务组合方法。利用功能参数之间的语义关联,建立一种Web服务语义功能属性描述模型,对那些在功能属性语义上具有关联性的Web服务,采用图路径搜索的方法来完成服务组合,从而在服务组合阶段缩小参与服务组合的范围,提高了组合服务的效率和有效性。     

Discovering internal social relationship for influence-aware service recommendation

Existing approaches, such as semantic content-based or Collaborative Filtering-based recommendations, fail to exploit social aspects of services because services lack social relationships and do not consider social influence. In this paper, we propose a methodology for connecting distributed services in a global social service network (GSSN) to facilitate discovering internal social relationship for social influence-aware service recommendation. First, we propose a novel platform for constructing a GSSN by linking distributed services with social links based on quality of social link. We then propose a flexible model of the effective awareness of social influence, which provides a quantitative measure of the strength of influence between services. Next, a novel social influence-aware service recommendation approach is proposed based on GSSN using internal social relationship among services. The experimental results demonstrated that our new approach can solve the service recommendation problem with a low usage threshold and high accuracy, where the user preferences are exploited by a recommend-as-you-go method.     

Dynamic Service Composition in Pervasive Computing

Service-oriented architectures (SOAs) promise to provide transparency to resource access by exposing the resources available as services. SOAs have been employed within pervasive computing systems to provide essential support to user tasks by creating services representing the available resources. The mechanism of combining two or more basic services into a possibly complex service is known as service composition. Existing solutions to service composition employ a template-matching approach, where the user needs are expressed as a request template, and through composition, a system would identify services to populate the entities within the request template. However, with the dynamism involved in pervasive environments, the user needs have to be met by exploiting available resources, even when an exact match does not exist. In this paper, we present a novel service composition mechanism for pervasive computing. We employ the service-oriented middleware platform called pervasive information communities organization (PICO) to model and represent resources as services. The proposed service composition mechanism models services as directed attributed graphs, maintains a repository of service graphs, and dynamically combines multiple basic services into complex services. Further, we present a hierarchical overlay structure created among the devices to exploit the resource unevenness, resulting in the capability of providing essential service-related support to resource-poor devices. Results of extensive simulation studies are presented to illustrate the suitability of the proposed mechanism in meeting the challenges of pervasive computing user mobility, heterogeneity, and the uncertain nature of involved resources.     

Web services lookup: a matchmaker experiment

UDDI is a standard registry for Web services, but so far its search functionality has been limited to keyword search. These authors propose a UDDI enhancement called Matchmaker, which supports semantic service capability discovery. Since September 2003, they have deployed Matchmaker in one of four official UDDI registries operated by NTT-Communications. In this article, they introduce Matchmaker and illustrate client tools that lower the threshold for using semantics in service discovery. Experiments show that Matchmaker search consumes about 5 seconds more time than a typical keyword-based search. The authors also collected user information through questionnaires and by observation of search behavior.