Duygu Çelik

Discovery and Scoring of Semantic Web Services based on Client Requirement(s) through a Semantic Search Agent

This paper shows a searching mechanism to discover semantic Web services satisfying client requirements. The increase in Web services and lack of semantic base in search mechanisms of UDDI make it difficult for clients to find a required Web service. We developed a system which uses a semantic search agent (SSA) to discover required Web services from Web and selects them according to the client requirements then presents them as a result page. The system uses Ontology Web Language for services (OWL-S), which allows semantic description of Web services and hence, the semantic search agent is able to understand predefined concepts of semantic Web services, extract necessary information and decide on the requirement of a service for a client. The system combines complimentary aspects of two research topics (smart Web query engine and matchmaking algorithm of OWL-S/UDDI matchmaker) to facilitate the provision of Web services to a client

A broker-based semantic agent for discovering Semantic Web services through process similarity matching and equivalence considering quality of service

The lack of semantic descriptions for “web service properties” makes it difficult to find suitable web services. Current solutions are mostly based on broker/mediator agent systems. However, these techniques are syntactical, rather than semantics oriented. This article presents a semantic matching approach for discovering Semantic Web services through a broker-based semantic agent (BSA). The BSA includes knowledge-bases and several processing steps. The BSA’s knowledge-bases are concept, task, and process ontologies built to describe both functional and non-functional parameters of services. The BSA executes semantic-based matching algorithms to discover similar services through the semantic matching step, process equivalence task, and matching of quality of service parameters. Relevant services are ranked by client preferences utilizing the semantic descriptions of available services. Other matchmaker studies are reviewed and compared with the BSA. Performance of the BSA algorithm is compared with SAM using published data and an experimental setup. The results indicate that our approach is better and more effective in some respects.

Provision of semantic web services through an intelligent semantic web service finder

This paper shows a searching mechanism to discover Semantic Web Services satisfying client requirements. The increase in web services and lack of semantic base in search mechanisms of UDDI make it difficult for clients to find a required web service. We developed a system which uses a Semantic Search Agent (SSA) to discover suitable web services according to client requirements then presents them as a result page. The system uses Ontology Web Language for Services (OWL-S), which allows semantic description of web services. Hence, the SSA is able to understand predefined features of Semantic Web Services, extract necessary information, and decide on which services would meet the service requirement of a client. The system retargets and combines complimentary aspects of two research topics (Smart Web Query Engine and Matchmaking Algorithm of OWL-S/UDDI Matchmaker) to facilitate the provision of web services to a client.

Towards an Information Extraction System Based on Ontology to Match Resumes and Jobs

While Internet takes up by far the most significant part of our daily lives, finding jobs/employees on the Internet has started to play a crucial role for job seekers and employers. Online recruitment websites and human resources consultancy and recruitment companies enable job seekers to create their résumé, a brief written formal document including job seekers basic information such as personal information, educational information, work experience and qualifications in order to find and apply for desirable jobs, whereas they enable companies to find qualified employees they are looking for. However résumés may be written in many ways that make it difficult for online recruitment companies to keep these data in their relational databases. In this study, a project that Kariyer.net (largest online recruitment website in Turkey) and TUBITAK (The Scientific and Technological Research Council of Turkey) have been jointly working is proposed. In this mentioned project, a system enables free structured format of résumés to transform into an ontological structure model. The produced system based on ontological structure model and called Ontology based Résumé Parser (ORP) will be tested on a number of Turkish and English résumés. The proposed system will be kept in Semantic Web approach that provides companies to find expert finding in an efficient way.

An ontology-based information extraction approach for résumés

A Curriculum Vitae (CV) or a resume, in general, consists of personal information, education information, work experience, qualifications and preferences parts. Scanning or making structural transformation of the millions of free-formatted resumes from the databases of companies / institutions with human factor will result in the loss of too much time and human effort. In the literature, a limited number of studies have been done to change the resumes of the free-format to a structural format. The overall objective of the study is to infer required information such as users experience, features, business and education from resumes of the potential user of a human resources system. In this article, we proposed an ontology driven information parsing system that is planned to operate on few millions of resumes to convert them structured format for the purpose of expert finding through the Semantic Web approach.

Finding Suitable Course Material through a Semantic Search Agent for Learning Management Systems of Distance Education

Developing technology and increasing usage of computers around the world make Internet a convenient tool for Distance Education (DE) systems. Learning Management Systems-(LMSs) of DE around the world serve content-based courses to students/users via static pages on the Web. Additionally, querying for specific course content of an entire course in LMS is only possible by syntactic-based search agents which limit the search. Therefore, it is thought that querying of contents through semantic-based approaches would make LMSs more helpful for a student/user through the Semantic Web (SW) approach. Queries can be meaning based and this can enable the system to make meaningful inference in human-computer interaction. In this article, we propose a system architecture that performs semantic -- based searches through an agent in order to plan student-based schedule of course documents automatically according to students performance in the course of a semester. OWL language of the SW technology is used during the development of the ontology of the LMS system that is used as a knowledgebase and queried to obtain required data. In this article, we concentrate on developing the system as a module for a LMS currently in use.

Ontology-Based Matchmaking and Composition of Business Processes

This chapter shows how it is possible to use agents and Semantic Web technologies to deal with dynamic composition of business processes via an agent-based workflow system. The aim of the system is to discover composable processes at first among heterogeneous business processes that are running possibly under different Web servers and then execute them in the order specified by a planner to reach a complex requested goal. We proposed a framework of an Inference-based Semantic Composition Agent (SCA) of atomic business processes that employs process similarity matching and inference techniques. SCA synthesizes new services from existing ones in an automatic fashion. A powerful matching mechanism is needed to find fitting tasks in order to attain the required composition. An innovative Semantic Matching Step (SMS) of SCA helps to find the fitting tasks while constituting workflow to achieve required composition. Additionally, SCA composes available OWL-S atomic processes utilizing Revised Armstrong’s Axioms (RAAs) in inferring functional dependencies. Experiments show that SCA System produces atomic process sequences as a workflow in achieving the required composition plan that satisfies user’s requirements as a complex task. The novelty of the SCA System is that for the first time Armstrong’s Axioms are revised and used for semantic-based planning and inferencing of services.

Semantic QoS Model for Extended IOPE Matching and Composition of Web Services

UDDI and WSDL do not provide sufficient grounds to find appropriate Web services at the required accuracy and quality of service (QoS) level by the consumer. This article discusses a semantic search agent (SSA) approach that discovers appropriate Web services according to semantic description. The descriptions comprise QoS requirements and input/output information of fetched Web services according to consumer requirements. This study considers a broker or dispatcher model which consists of a QoS broker-based scheme by a multi-class queuing model. We depicted a new system that is an extension of the SSA to find appropriate Web services according to consumer request based on matching of input/output and QoS information of Web services; then compose them according to consumer requirements through semantic Web and ontology.

Searching Semantic Web Services: An Intelligent Agent Approach Using Semantic Enhancement of Client Input Term(s) and Matchmaking Step

This paper proposes a smart mechanism to discover semantic Web services satisfying client requirements. The increase in Web services and lack of semantic base in search mechanisms of UDDI make it difficult for clients to find a required Web service. It is proposed to develop an intelligent agent to discover required Web services from Web. The system uses OWL-S for describing semantics of Web services and discovers appropriate semantic Web services through these semantic descriptions. OWL-S allows semantic description of Web services and hence, the intelligent agent is able to understand predefined concepts of semantic Web services, extract necessary information and decide on the requirement of a service for a client. The intelligent agent interacts with client and semantic Web services. The system proposed combines aspects of two research topics (smart Web query engine and matchmaking algorithm of OWL-S/UDDI matchmaker) to facilitate the provision of Web services to a client

A Safety Food Consumption Mobile System through Semantic Web Technology

Over 3,000 compounds are being added to processed food. These compounds have numerous effects on food: add color, stabilize, texturize, preserve, sweeten, thicken, add flavor, soften, emulsify, and so on. According to a recent report by the World Health Organization, governments have lately focused on legislation to reduce such ingredients or compounds in manufactured foods for they might have side effects causing health risks such as the heart disease, cancer, diabetes, allergens, obesity, etc. Safety in food consumption especially by patients of risk groups have become crucial for such health problems are in the top ten ranked health risks around the world. By supervising what and how much to eat as well as what not to eat, we can maximize a patients life quality by avoiding unhealthy ingredients or compounds. In helping patients take control of their safe food consumption, we need smart personal e-health systems. Smart personal e-health systems with advanced knowledge management technology can provide suggestions of food appropriate for consumption by individuals. Accessing annotations in the ontology knowledgebase of food appropriate to their personal health condition can be provided. This article discusses one such software application, namely the Safety Food Consumption Mobile System, employing Semantic Web Technology.