Scientific Programming


This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Discovery of semantic Web services is a heavyweight task when the number of Web services or the complexity of ontologies increases. In this paper, we present a new logical discovery framework based on semantic description of the capability of Web services and user goals using F-logic. Our framework tackles the scalability problem and improves discovery performance by adding two prefiltering stages to the discovery engine. The first stage is based on ontology comparison of user request and Web service categories. In the second stage, yet more Web services are eliminated based upon a decomposition and analysis of concept and instance attributes used in Web service capabilities and the requested capabilities of the client, resulting in a much smaller pool of Web services that need to be matched against the client request.

Automatic Matchmaking of Web Services

Semantic matching represents a fundamental technique in many applications in areas such as resource discovery, data integration, data migration, query translation, peer to peer networks, agent communication, schema and ontology merging. It using is also being investigated in other areas such as event processing. In fact, it has been proposed as a valid solution to the semantic heterogeneity problem, namely managing the diversity in knowledge.

Interoperability among people of different cultures and languages, having different viewpoints and using different terminology has always been a huge problem.

It enhances the improved bipartite graph based web s ervice matching. But the different matcher may semantic web service composition using clustering and ant colony optimization. This novel architecture solved the It improves the improved Bipartite graph based matching by considering multiple similarity metric.

Therefore, enhancing web service discovery WSD method will improve the searching performance. In this paper, we firstly discuss and review some existing web service discovery approaches and identify their limitations. Subsequently, we propose a web service discovery method for cloud-based mobile application by using multi-level clustering technique to improve performance by reducing the searching scope.

Our web service discovery architecture is able to increase the discoverability of more accurate web services based on user’s preferences. Meanwhile, user preference Quality of Services QoS attributes are also used for ranking procedure to allow user to decide the quality of the mobile application. The experimental results show that our approach is able to increase the searching performance and provide a reliable list of selection for users.

Web service discovery; cloud-based mobile application; multi-level clustering; QoS-based ranking; user-based QoS Access to the content you have requested requires one of the following:

Proceedings of ICWS 07

This paper shows a matchmaking algorithm to discover Semantic Web Services that are satisfying client requirements. At least fifty percent average gain in search relevancy is obtained when our matchmaking algorithm is applied to WSs that are actually matching the chosen fuzzy semantic theme. Introduction One of the crucial steps in an efficient Web service search is to understand what users mean in their request. The search request is usually in the form of natural language.

Using graph theory, we analyze the topological landscape of web service networks formed by real-world data set, either downloaded from web service repositories or crawled by a search engine. We first propose a flexible framework to study syntactic web service matchmaking in a unified manner.

The matched response interface instance and Web service name that are stored in the matched Response column family can be obtained from column family response interface in ontology table. The last column family Request Inteface stores the request that belongs to the Web service producing the response interface in the matched Response. The Request Inteface can be obtained from the table, which mainly manages the interface information.

After fetching all matched interfaces, the next step is to find the matching relation among Web services by using Web service match algorithm called SBMWS as shown in Algorithm 1. Function Mapper key,value 2. Ouput wsn, matched Interface ; 3. Function Reducer wsn, matched Interfaces 5. Output Null, matchedResult ; 9. EndReducer According to Algorithm 1, the worst case of the time complexity is about O n2.

The function Mapper is used to obtain the matched interface among Web services, and then the algorithm can find the best matched among services since it’s possible that the response interfaces of a single Web service cannot satisfy all request interfaces. To accomplish the complex task, each simple Web service must be composed together with QoS reaching the global optimization. Figure 3 presents the procedure of Web service composition. Figure 3 Procedures of Web Service Composition We use the Petri net to describe the Web service composition graph, and the token in this graph denotes the customer’s response requirement.

The response place can be considered as the start point.

Journal of Healthcare Engineering

Correspondence should be addressed to Lei Tang ; moc. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Service matching aims to find the information similar to a given query, which has numerous applications in web search. Although existing methods yield promising results, they are not applicable for transportation.

In this paper, we propose a multilevel matching method based on semantic technology, towards efficiently searching the traffic information requested.

The semantic web services (SWSs) discovery is the process of finding a service that can possibly satisfy the user requirements, choosing between several services, and composing services to form a .

A search is formulated as a problem of computing a maximum matching in pairwise bipartite graphs formed from query and repository schemas. The edges of such a bipartite graph capture the semantic similarity between corresponding attributes of the schema based on their name and type semantics. Tight upper and lower bounds are also derived on the maximum matching that can be used for fast ranking of matchings whilst still maintaining specified levels of precision and recall.

Field of Invention The present invention relates generally to the field of searching repositories for semantically related schemas. More specifically, the present invention is related to mechanisms for searching XML repositories for semantically related schemas representing structured metadata. Discussion of Prior Art XML is fast becoming the de facto standard for representing structured metadata in databases and Internet applications. It is now possible to express several kinds of metadata such as relational schemas, business objects or web services through XML schemas.

As XML starts to be used more ubiquitously in the industry, large metadata repositories are being constructed ranging from business object repositories, UDDIs Universal Description Discovery and Interaction to general metadata repositories. This has given rise to the need for efficient search mechanisms for the search of such XML repositories in several application domains, for example, in business process modeling, analysts want to search for appropriate services to help compose their business process flows.

In data warehousing, warehousing specialists would like more automatic ways to identify related schemas for merging than the current laborious GUI-directed processes offered by warehousing tools. Finally, an increasing number of organizations are putting their business competencies as a collection of web services. It is conceivable that other users could integrate them to create new value-added services in ways that were not anticipated by their original developers.

Journal of Advanced Transportation

To fully fulfill the modularity and loosely coupled characteristics of P2P semantic mapping paradigm proposed in our previous work[1], a mapping creation method based on semantic discovery is presented to avoid a time-consuming and labor-intensive artificial mapping creation process. This method creates semantic mapping between peer node models by establishing the semantic relations between elements from different peer node models. Semantic relative candidates are captured through the correspondence semantic matching process including concepts matching process, attributes matching process, relations matching process, concepts and relations matching process, and concepts and attributes matching process.

To improve the degree of automation for mapping establishment, the hybrid semantic discovery approach is used in the semantic discovery process. The image matching technology is very important technology in computer vision.

FIG. 6 is a schematic diagram illustrating a second example of semantic schema matching for web service The correspondence between the source and target attributes can be described as a matching in the bipartite graph. A matching is a set of edges of the bi-partite graph such that at most one edge is incident on either source or target.

A very selective summary 4. Mashup is not simply about the AJAX technologies, rather, it is typically related to reuse the data and other services from other web side and web applications. There are many ways to build up the mashup. This half-day tutorial will focus on using XML and JSON format of data and service and will introduce the following to the participants: What Mashup is about. The existing Mashup web sites and applications. The Mashup design and architecture which include the client-side mashups and server-side mashups.

The existing mashup technologies. At the completion of this tutorial, participants will learn the latest mashup trends and how to architecture, build and manage the Mashup by using the existing tools, data and services for their applications.

Study of an Algorithm of Web Service Matching Based on Semantic Web Service

Suite Washington DC Claims: A method for semantic service registration and query based on WordNet, characterized in that the method comprising the specific steps of: The method for semantic service registration and query based on WordNet as described in claim 1, characterized in that the semantic annotation of Web services in the said Step 1 is based on an interface information of input and output function in the WSDL document to annotate semantic ontology and form a Web Service Semantic Description Document WSDL-S, wherein, the semantic ontology adopts a WordNet ontology library.

The ability to dynamically discover and invoke a Web service is a critical aspect of service oriented architectures. An important component of the discovery process is the matchmaking algorithm itself. In order to overcome the limitations of a syntax-based search, matchmaking algorithms based on semantic techniques have been proposed. Most of them are based on an algorithm originally proposed.

Semantic Matchmaking for Job Recruitment: Our aim in this work is to propose an ontology-based hybrid approach to effectively match job seekers and job advertisements. The approach uses a deductive model to determine the kind of match between a job seeker and an advertisement, and applies a similarity-based approach to rank applicants.

Semantic Matching, Recruitment, Skill Ontology 1 Introduction In human resource management it is often necessary to locate and match individuals and positions. Examples of such tasks include human resource recruiting, selecting individuals for teams based on different skills and qualifications, and finding the right expert to acquire information or to learn from within an organization.

Currently, for human resource recruiting, the Internet is being mainly used to place online job advertisements, to perform resume search, and to acquire information about skills and competencies of individuals [4].

Abstract service logic-based interactive semantic Web service dynamic combination method

UDDI provides limited search facilities allowing only a keyword-based search of businesses, services, and the so called tModels based on names and identifiers. This category-based keyword-browsing method is clearly insufficient. This improvement enables software agents or search engines to automatically find appropriate Web services via ontologies and reasoning algorithm enriched methods.

However, the high cost of formally defining to the heavy and complicated services makes this improvement widespread adoption unlikely.

Later an algorithm of service discovery based on bipartite matching of semantic message similarity is proposed, which can fully use the semantic information of the interfaces of Web services. The method is easy to implement because of using WSDL standard instead of some specific service .

The authors have declared that no competing interests exist. Conceived and designed the experiments: Received Nov 19; Accepted Apr Associated Data All relevant data are within the paper. The AWSCS is a system to implement different approaches for automatic composition of Web services and also to execute the resulting flows from these approaches. Aiming at demonstrating the results of this paper, a scenario was developed, where empirical flows were built to demonstrate the operation of AWSCS, since algorithms for automatic composition are not readily available to test.

The results allow us to study the behaviour of running composite Web services, when flows with the same functionality but different problem-solving strategies were compared.

Semantic Matchmaking for Job Recruitment – CEUR Workshop …

At the heart of most service discovery mechanisms is a matchmaking algorithm that matches a semantic query to a set of compatible web service advertisements. These advertisements also describe service semantics as a set of OWL-S terms. Most current matchmaking algorithms are based on semantic matching of input and output terms alone.

Improved matchmaking algorithm for semantic Web services based on bipartite graph matching. In Proceedings of the International Semantic Web Conference. 7.

This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services.

The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules.

The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: Introduction Web services WS composition is a method used to combine existing WS from heterogeneous systems to build more complicated business processes that match with user requirements. WS composition also accommodates the development of systems capable of automatic execution of multiple individual WS simultaneously [ 1 ].

However, these technologies do not offer well-defined semantic and expressive capability for solving semantic service discrepancies that occur due to disagreement in the meaning, interpretation, or intended use of service information. In most cases, this situation drives the challenge of creating an automated WS composition system that focuses on solving the problems of WS heterogeneities.

These problems necessitate semantic matching of input and output parameters to combine multiple relevant services. Richer semantics for WS provide greater automation of selection, composition, and invocation of heterogeneous services. Semantic Web Services SWS [ 4 , 5 ] have emerged to facilitate automation and dynamism in WS discovery, selection, composition, and monitoring.

A Hadoop-based Approach for Efficient Web … – Semantic Scholar

August 12, ; Accepted: January 05, ; Published: Thus, finding appropriate services quickly and accurately is considered as hard as searching a needle in the haystack Garofalakis et al. Many efforts have been made to settle this problem and applying service clustering technique for service discovering is a mainstream idea in recent years. Generally speaking, the process of clustering services starts from parsing web service describing documents such as WSDL and extracting features and then groups web services into functionality-based clusters according to a particular methods for clustering Elgazzar et al.

The main method for service clustering focuses on the similarity among services.

The semantic web services (SWSs) discovery is the process of finding a service that can possibly satisfy the user requirements, choosing between several services, and composing services to form a .

Automatically composing services, however, is a challenging problem since it is unlikely that web services derived from widely distributed sources use similar terminology or structure in their abstract data types to enable direct chaining. The invention presents an approach to physically compose a specified set of services by semantically matching schemas derived from the API specification of source and destination services Specifically, the invention models the correspondence between schemas as a problem of finding a maximum matching in a bipartite graph formed from the attributes of source and destination API schemas.

The weights on the edges of the graph represent the similarity between the pairs of source and target attributes and are derived using cues, including, lexical and ontological similarity in names, their relation in a reference type hierarchy, conceptual grouping reflected in the structure of the schemas, and the existence of mapping functions between the attributes. The best possible matching between source and destination attributes is derived using a cost scaling network flow algorithm.

A motivating example is drawn from the domain of Life Sciences where the use of web services is becoming prevalent. With the sequencing of the human genome, a greater challenge now faces the scientists: With advances in sequencing techniques and the advent of Gene Chips, increasingly large amounts of data is becoming available on a worldwide basis as a combination of public and private genome databases. In addition, increasing number of analytic tools are becoming available, including both commercial e.

In most cases, the tools developed are meant to be standalone applications or deployed over the web. In addition, each tool uses proprietary data formats so that scientists often have to do a lot of document preparation before they can use such tools. For example, a diagnosis that combines information from gene expression, blood test, and x-ray data may need to access, analyze and combine information in three separate data sources.

To satisfactorily address the needs of scientists, therefore, an information integration framework is needed that can pull together both life sciences data and analytic applications from disparate sources.

AALG5: Flow networks, maximum bipartite matching example

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