published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy

published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

Reviews why it is important to search blogs for competitive intelligence, reputation management, and brand image management. Describes the structure of blogs and how to format searches in several search engines to effectively retrieve this information.

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Ontology has been developed to offer a commonly agreed understanding of a domain that is required for knowledge representation, knowledge exchange and reuse across domains. Therefore, ontology organizes information into taxonomies of terms (i.e., concepts, attributes) and shows the relationships between them. In fact, it is considered to be helpful in reducing conceptual confusion for users who need to share applications of different kinds, so it is widely used to capture and organize knowledge in a given domain. Although ontologies are considered to provide a solution to data heterogeneity, from another point of view, the available ontologies could themselves introduce heterogeneity problems. In order to deal with these problems, ontologies must be available for sharing or reusing; therefore, semantic heterogeneity and structural differences need to be resolved among ontologies. This can be done, in some cases, by aligning or matching heterogeneous ontologies. Thus, establishing the relationships between terms in the different ontologies is needed throughout ontology alignment. Semantic interoperability can be established in ontology reconciliation. The original problem is called the ―ontology alignment‖. The alignment of ontologies is concerned with the identification of the semantic relationships (subsumption, equivalence, etc.) that hold between the constituent entities (which can be classes, properties, etc.) of two ontologies. In this thesis, an ontology alignment technique has been developed in order to facilitate communication and build a bridge between ontologies. An efficient mechanism has been developed in order to align entities from ontologies in different description languages (e.g. OWL, RDF) or in the same language. This approach tries to use all the features of ontologies (concept, attributes, relations, structure, etc.) in order to obtain efficiency and high quality results. For this purpose, several matching techniques have been used such as string, structure, heuristic and linguistic matchingtechniques with thesaurus support, as well as human intervention in certain cases, to obtain high quality results. The main aim of the work is to introduce a method for finding semantic correspondences among heterogeneous ontologies, with the intention of supporting interoperability over given domains. The approach brings together techniques in modelling, string matching, computation linguistics, structure matching and heuristic matching, in order to provide a semi-automatic alignment framework and prototype alignment system to support the procedure of ontology alignment in order to improve semantic interoperability in heterogeneous systems. This technique integrates some important features in matching in order to achieve high quality results, which will help when searching and exchanging information between ontologies. Moreover, an ontology alignment system illustrates the solving of the key issues related to heterogeneous ontologies, which uses combination-matching strategies to execute the ontology-matching task. Therefore, it can be used to discover the matching between ontologies. This thesis also describes a prototype implementation of this approach in many real-world case studies extracted from various Web resources. Evaluating our system is done throughout the experiments provided by the Ontology Alignment Evaluation Initiative. The system successfully achieved 93% accuracy for ontology matching. Finally, a comparison between our system and well-known tools is achieved so that our system can be evaluated.

Natural history collections house immense amounts of data, but the majority of data is only accessible by locating the collection label, which is usually attached to the physical specimen. This method of data retrieval is time consuming and can be very damaging to fragile specimens. Digitizing the collections is the one way to reduce the time and potential damage related to finding the collection objects. The Elm Fork Natural Heritage Museum is a natural history museum located at the University of North Texas and contains collections of both vertebrate and invertebrate taxa, as well as plants. This project designed a collection digitization workflow for Elm Fork by working through digitizing the Benjamin B. Harris Herbarium. The collection was cataloged in Specify 6, a database program designed for natural history collection management. By working through one of the museum’s collections, the project was able to identify and address challenges related to digitizing the museum’s holdings in order to create robust workflows. The project also produced a series of documents explaining common processes in Specify and a data management plan.