Ontology-based Web Research Articles

An Ontology Based Web Crawler with a Near-Duplicate Detection System to Improve the Performance of a Web Crawler

Purpose: The aim of the study is to examine how an ontology-based web crawler with a near-duplicate detection system improves the performance of a web crawler. Methodology: The experiment was carried out using secondary data from a sample web site which was used since crawling is an endless process. Using these two approaches, the ontology web crawler would search for relevant searches according to the search query of the user while the near-duplicate detection system would eliminate redundant data. Findings: It was observed that ontology web crawler performed better and faster than a normal crawler. It takes less execution time to search the web than other web crawlers. This is due to the fact that web documents are being filtered by the ontology web crawler such that only relevant web documents are retrieved according to the search query of the user. The relevant documents are further filtered by a near-duplicate detection system by removing web pages that are duplicates of each other and also remove near-duplicate web documents. This further reduces the number of web pages retrieved by the web crawler. This model saves on storage space because of the reduced number of web pages retrieved as it takes care of irrelevant and redundant web pages searched. Unique Contribution to Theory, Practice and Policy: The study recommends that the model can be improved to be dynamic by adding new relations that is the crawler should search for web pages related to the search even if they don’t contain the keywords searched. Domains and concepts should be added when visiting new web pages. Standardization of weights needs to be done because as of now experts assign weights to terms according to the area of expertise and knowledge.

Version [2.0.0]-[ENTIRETY—sEmanNTIc pRovisioning and govErning ioT devices in smart energY domain]

ENTIRETY 1 is a web application for governing and provisioning IoT devices. Due to the rapid evolution and digitization of energy systems, energy domain ontology is required to manage the data in a structured way. This paper presents the ontology-based web application ENTIRETY 2, which is the updated version of ENTIRETY 1. This updated version provides an interface for data collection and transmission. The data collected by the IoT device are provided to the ICT platform according to the ontology. ENTIRETY 2 overcomes the challenges of the mapping between the different network protocols and automates the generation of JSON-LD based on ontology files. Therefore, the ENTIRETY 2 can be easily extended to support other ontologies.

Context-Based Support to Enhance Developers’ Learning of Software Security

Software security is an ongoing problem, largely due to a lack of security knowledge among software developers from diverse backgrounds. To counter this, security experts are attempting to offer a broad range of knowledge resources to enlighten developers about increasing cybersecurity threats. Unfortunately, the abundance of knowledge resources does not seem to have much of an impact on reducing the issue of software security. The ineffective teaching and learning approaches for software security have created difficulties for developers in learning security knowledge. This research employs a four-cycle of Design Science Research Methodology (DSRM) to integrate necessary elements in the development of a context-based learning system for security education and learning. The final artifact is an ontology-based web application that facilitates a contextualized learning process by providing security knowledge through contextual software cases. Through evaluation in pedagogical and software development environments, it is proven to contribute a viable solution to the problem domain. While these results are positive, the innovative context-based artifact benefits not only the domain of software engineering but also other educational fields, such as information security and computer security.

An ontology-based web decision support system to find entertainment points of interest in an urban area

ABSTRACT In recent years, decision support systems (DSSs) have successfully deployed ontologies in their architecture. The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities. Visitors from throughout Iran travel to different cities and regions every year, and they need help making their choices. Some of these tourists are unable to visit the beautiful areas of the destination city due to a lack of awareness. In this study, we design an ontology-based spatial DSS to find entertainment and tourism centers in Arak, Iran. The objective is to provide users with recommendations appropriate for the location, time, age group, type of activity, and other factors. In this model, the demands and concerns of tourists have been managed by creating a domain Web Ontology Language (OWL) for entertainment centers as a knowledge base in the Protégé environment. The developed web-based DSS operates on a client-server architecture using technologies such as Werkzeug and Flask. As a result, it makes it possible to ontology reasoning based on the HermiT engine to choose the right center and conduct a semantic search on classes related to the appropriate point of interest. The main distinction between the proposed methodology and the previous studies on spatial DSS is that criteria are object properties in an ontology. Therefore, decision support relies on real-time reasoning rather than transforming criteria into geospatial layers. The evaluation results confirmed efficient interaction with this system, purposeful information retrieval, and rapid decision-making process. The results also indicated that searching for a POI (point of interest) in the study area using the developed system is at least 30% more successful than a search engine or social media. Moreover, to overcome the cold start problem, the proposed technique might be utilized in conjunction with the POI recommender systems.

Ontology-based Web Map

Ontology-based Web Map

An Improved Methodology for Collaborative Construction of Reusable, Localized, and Shareable Ontology

Interlocking Institutional Worlds (IWs) is a concept explaining the need to interoperate between institutions (or players), to solve problems of common interest in a given domain. Managing knowledge in the IWs domain is complex; however, promoting knowledge sharing based on standards and common terms agreeable to all players is essential and is something that must be established. In this context, ontologies, as a conceptual tool and a key component of knowledge-based systems, have been used by organizations for effective knowledge management, better decision-making, and interoperability among diverse institutions of an IWs domain. The development of ontology involves structural and logical complexity, and requires a well-designed, mature, and widely accepted methodology, to ensure its reliability. Many methodologies for ontology development have been proposed by several researchers; however, most of the developed methodologies have not included several important phases. Furthermore, several methodologies have not provided the complete details of the techniques and activities involved in the ontology construction process. Fewer details make it difficult to follow a methodology for designing ontologies. This study aims to compare existing methodologies based on sixteen important criteria and proposes an improved methodology for ontology development for IWs domains. The proposed methodology has included several important phases such as the Estimation of Human Resources, Re-engineering and Re-using of Resources, Collaborative Ontology Construction, the Conceptualization of both Endurants and Perdurants, Localization of an Ontology, Ontology Integration and Merging, Support for Interoperability, Versioning of an Ontology, and Ontology Population. The proposed methodology has been applied to design an OntoWM domain ontology for the Waste Management (WM) domain. The evaluation of the proposed methodology has been made by utilizing the designed OntoWM domain ontology in an ontology-based web application called SmartBinAnalytics. SmartBinAnalytics has been built using OntoWM, Java Server Pages (JSP), Jena Application Programming Interface (API), and MySQL. The proposed methodology can be used for the construction of domain ontologies in any IWs domain.

A Framework for Automatic Categorization of Social Data Into Medical Domains

Nowadays, everyone is surrounded by a large volume of data which is generated from multiple sources. Every day 2.5 quintillion bytes of data are created worldwide. It is a very complicated task to manage and extract useful information from social media platforms. As people are more interested in seeking online health guidance, the medical textual data created by patients, healthcare professionals, and medical staff are expanding fast. In order to address this challenge, an ontology-based approach is used to annotate the medical domain data in this article. We have considered Twitter as our social media platform to filter the medical data from the general category data. In this article, we have used the Open Biomedical Annotator ( OBA ), which is an ontology-based Web service that annotates raw text with biomedical ontology concepts based on their textual metadata. Domain-specific knowledge is gathered by using MedlinePlus Health Topics and National Drug Data File ( NDDF ) ontologies licensed under the U. S. National Library of Medicine ( UMLS ), which will filter out all medical related terms. Furthermore, these medical terms are stored in a medical term database, which will then be forwarded to the UMLS REST Application Programming Interface ( API ) that provides important entities, such as Concept Unique Identifier ( CUIs ), semantic relations, attributes, definitions, and much more under the subset of SNOMEDCT_US which is the most precise and comprehensive health terminology platform in the world.

Ontology-Based Design of the Learner’s Knowledge Domain in Electrical Engineering

Abstract This research addresses some personalization aspects of education in electrical engineering. Its goal is to help students and educators evaluate the complexity of the disciplines they have chosen for studying and optimize the order of the learned courses and topics. A new instrument, namely, an educational thesaurus, is presented and its assembling procedure is shown. The offered educational thesauri implemented in the labs and integrated in the exercises have become smart platforms suitable for design and management of the students’ individual knowledge domains. The ontology-based Web manuals in Electronics and Power Electronics for the Bachelor study cycle have been introduced. An example of ontology graph to be applied within the Master study cycle has been developed and explained in the paper. According to the authors’ investigation, the decrease of stress caused by the new educational environment and achievement of success in learning were observed thanks to the individual knowledge domain organization proposed in this study.

SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes

BackgroundDespite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ontologies are only available in English, and cannot be readily applied to other languages, due to fundamental linguistic differences. However, semantic resources are required to design semantic indexes and transform biomedical (text)data into knowledge for better information mining and retrieval.ResultsWe present the SIFR Annotator (http://bioportal.lirmm.fr/annotator), a publicly accessible ontology-based annotation web service to process biomedical text data in French. The service, developed during the Semantic Indexing of French Biomedical Data Resources (2013–2019) project is included in the SIFR BioPortal, an open platform to host French biomedical ontologies and terminologies based on the technology developed by the US National Center for Biomedical Ontology. The portal facilitates use and fostering of ontologies by offering a set of services –search, mappings, metadata, versioning, visualization, recommendation– including for annotation purposes. We introduce the adaptations and improvements made in applying the technology to French as well as a number of language independent additional features –implemented by means of a proxy architecture– in particular annotation scoring and clinical context detection. We evaluate the performance of the SIFR Annotator on different biomedical data, using available French corpora –Quaero (titles from French MEDLINE abstracts and EMEA drug labels) and CépiDC (ICD-10 coding of death certificates)– and discuss our results with respect to the CLEF eHealth information extraction tasks.ConclusionsWe show the web service performs comparably to other knowledge-based annotation approaches in recognizing entities in biomedical text and reach state-of-the-art levels in clinical context detection (negation, experiencer, temporality). Additionally, the SIFR Annotator is the first openly web accessible tool to annotate and contextualize French biomedical text with ontology concepts leveraging a dictionary currently made of 28 terminologies and ontologies and 333 K concepts. The code is openly available, and we also provide a Docker packaging for easy local deployment to process sensitive (e.g., clinical) data in-house (https://github.com/sifrproject).

Ontology-based Decision Support System with Analytic Hierarchy Process for Tour Package Selection

The popularity of Internet and growing B2C electronic commerce nowadays make product or service information easy to be acquired. However, making an optimal choice from the various alternative products becomes a laborious process. In this paper, an ontology-based Decision Support System (DSS) with Analytic Hierarchy Process (AHP) was proposed for the specific application of tour package selection. The system is composed of two subsystems, the product gatherer and the decision maker, which are used to find out right products and make an expected choice respectively. In the product gatherer subsystem, an ontology-based web service architecture with Web Ontology Language (OWL) was established for the semantic content processing of product information. The Simple Object Access Protocol (SOAP) is utilized to establish the communication interface and gather XML-based contents through Remote Procedure Calls (RPC) between the system and the database servers of travel agencies. In the decision maker subsystem, the Analytic Hierarchy Process is utilized to make an optimal decision for satisfying the requirement given by the consumer. The system aims to help consumers to avoid falling into decision-making hesitation and get an expected choice from various and similar products.

Ontology-based web services classification for registration and discovery of web services

Web services become increasingly important in the world of internet. Thus, users need to access and effectively share web services. The centralised UDDI is a less robust structure and does not support a large number of web services. If the distributed environment is introduced into the UDDI, there will be a rapid increase in services with minimisation of resource consumption. Accordingly, mechanisms are needed for efficient selection of the appropriate instance of the web service in terms of factors like quality and performance. Distribution mechanisms, clustering and classification are necessary for efficient selection of the appropriate web service to the customer needs. In this paper, we propose a shared repository (ontology) which is produced by clustering of web services. This ontology can be exploited by the UDDI for publishing and discovering web services. A matching algorithm is also proposed to show how to perform this operation. A prototype tool has been developed to support experiments that have been carried out to evaluate and show the efficiency of our matching algorithm. We also introduce a comparative analysis to show the effectiveness of our approach compared to existing works.

Ontology-based web services classification for registration and discovery of web services

Web services become increasingly important in the world of internet. Thus, users need to access and effectively share web services. The centralised UDDI is a less robust structure and does not support a large number of web services. If the distributed environment is introduced into the UDDI, there will be a rapid increase in services with minimisation of resource consumption. Accordingly, mechanisms are needed for efficient selection of the appropriate instance of the web service in terms of factors like quality and performance. Distribution mechanisms, clustering and classification are necessary for efficient selection of the appropriate web service to the customer needs. In this paper, we propose a shared repository (ontology) which is produced by clustering of web services. This ontology can be exploited by the UDDI for publishing and discovering web services. A matching algorithm is also proposed to show how to perform this operation. A prototype tool has been developed to support experiments that have been carried out to evaluate and show the efficiency of our matching algorithm. We also introduce a comparative analysis to show the effectiveness of our approach compared to existing works.

An ontology-based web service framework for construction supply chain collaboration and management

Purpose – The purpose of this paper is to present a framework for integrating construction supply chain in order to resolve the data heterogeneity and data sharing problems in the construction industry. Design/methodology/approach – Standardized web service technology is used in the proposed framework for data specification, transfer, and integration. Open standard SAWSDL is used to annotate web service descriptions with pointers to concepts defined in ontologies. NoSQL database Cassandra is used for distributed data storage among construction supply chain stakeholders. Findings – Ontology can be used to support heterogeneous data transfer and integration through web services. Distributed data storage facilitates data sharing and enhances data control. Practical implications – This paper presents examples of two ontologies for expressing construction supply chain information – ontology for material and ontology for purchase order. An example scenario is presented to demonstrate the proposed web service framework for material procurement process involving three parties, namely, project manager, contractor, and material supplier. Originality/value – The use of web services is not new to construction supply chains (CSCs). However, it still faces problems in channelizing information along CSCs due to data heterogeneity. Trust issue is also a barrier to information sharing for integrating supply chains in a centralized collaboration system. In this paper, the authors present a web service framework, which facilitates storage and sharing of information on a distributed manner mediated through ontology-based web services. Security is enhanced with access control. A data model for the distributed databases is also presented for data storage and retrieval.

An ontology-based Web mining method for unemployment rate prediction

Unemployment rate is one of the most critical economic indicators. By analyzing and predicting unemployment rate, government officials can develop appropriate labor market related policies in response to the current economic situation. Accordingly, unemployment rate prediction has attracted a lot of attention from researchers in recent years. The main contribution of this paper is the illustration of a novel ontology-based Web mining framework that leverages search engine queries to improve the accuracy of unemployment rate prediction. The proposed framework is underpinned by a domain ontology which captures unemployment related concepts and their semantic relationships to facilitate the extraction of useful prediction features from relevant search engine queries. In addition, state-of-the-art feature selection methods and data mining models such as neural networks and support vector regressions are exploited to enhance the effectiveness of unemployment rate prediction. Our experimental results show that the proposed framework outperforms other baseline forecasting approaches that have been widely used for unemployment rate prediction. Our empirical findings also confirm that domain ontology and search engine queries can be exploited to improve the effectiveness of unemployment rate prediction. A unique advantage of the proposed framework is that it not only improves prediction performance but also provides human comprehensible explanations for the changes of unemployment rate. The business implication of our research work is that government officials and human resources managers can utilize the proposed framework to effectively analyze unemployment rate, and hence to better develop labor market related policies.

The Extended Algorithm of the Bipartite Graph Matching Semantic Web Service Discovery

In previous work, the ontology-based algorithm of bipartite graph matching semantic web service discovery was presented. But in these algorithms, the problem of finding augment path was not resolved very well. It will affect the recall rate and precision rate of web service discovery. In order to resolve these problems, this paper proposes an ontology-based bipartite graph matching semantic web service discovery algorithm, which extends the optimal bipartite graph matching algorithm. It uses the slack function to find the augment path in the equivalent sub graph. The algorithm also contributes to the improvement of the recall rate and precision rate of the service discovery.

Scalable optimization in grid, cloud, and intelligent network computing – foreword

Scalable optimization in grid, cloud, and intelligent network computing – foreword

PRIMES: an ontology-based web service for software risk management

This paper aims at building a system to aid, and in certain cases, perform the work of the project analysts. It deals with providing an ontology based web service to analyse each project based on the factors, relationships and constraints that constitute the respective project. Its main goal is to provide project analysts with a web service to aid them in identifying and assessing the risks involved in the project, allowing them to plan for avoiding, controlling and monitoring risks. The main motivation of the system is to provide a major incentive for the industry, by reducing the cost involved and the time spent on analysing projects, and removing the unnecessary resources spent on non-feasible projects. This proposed system aids risk analysts in analysing projects, products and services, and enhancing risk management techniques, thereby increasing the efficiency of the analytic process. It also performs the function of risk analytic for small scale and medium scale projects, and provides a scenario for risk analysts to compare current and previous projects.

An Efficient Ontology-based Semantic Web Services Composition Model for Peer to Peer Work

An Efficient Ontology-based Semantic Web Services Composition Model for Peer to Peer Work

Multi-agent ontology-based Web 2.0 platform for medical rehabilitation

Information technologies have played key roles in a wide range of medical settings such as hospital wards, operating rooms, emergency departments, and rehabilitation centers, rendering biomedical knowledge and data more accessible for human comprehension, comparison, analysis and communication. In this context, ontology has been recognized in the bioinformatics literature as a suitable technique for advancing knowledge and data representations in biomedicine. With the enhancement of automated reasoning and graphical visualizations, ontology-technology can assist human comprehensibility as well as mitigating the complexity inherent to this domain.Rehabilitation medicine has become an important part field in medicine, as distinct from preventive medicine, health care medicine and clinical medicine. In this article, we aim to address the ontological and epistemological issues of information services through the example of OntoRis, an ontology-based rehabilitation service OntoRis is designed to assist patients in acquiring actionable knowledge about his/her prescribed rehabilitation, and to expedite recovering through providing suggestions and advice drawn from evidence-based medicine. Moreover, OntoRis can also serve as an interactive learning platform for people who are interested in rehabilitation medicine.

The framework of a geospatial semantic web-based spatial decision support system for Digital Earth

While significant progress has been made to implement the Digital Earth vision, current implementation only makes it easy to integrate and share spatial data from distributed sources and has limited capabilities to integrate data and models for simulating social and physical processes. To achieve effectiveness of decision-making using Digital Earth for understanding the Earth and its systems, new infrastructures that provide capabilities of computational simulation are needed. This paper proposed a framework of geospatial semantic web-based interoperable spatial decision support systems (SDSSs) to expand capabilities of the currently implemented infrastructure of Digital Earth. Main technologies applied in the framework such as heterogeneous ontology integration, ontology-based catalog service, and web service composition were introduced. We proposed a partition-refinement algorithm for ontology matching and integration, and an algorithm for web service discovery and composition. The proposed interoperable SDSS enables decision-makers to reuse and integrate geospatial data and geoprocessing resources from heterogeneous sources across the Internet. Based on the proposed framework, a prototype to assist in protective boundary delimitation for Lunan Stone Forest conservation was implemented to demonstrate how ontology-based web services and the services-oriented architecture can contribute to the development of interoperable SDSSs in support of Digital Earth for decision-making.