Agnieszka Konys

Approach to practical ontology design for supporting COTS component selection processes

The COTS (Commercial Off-The-Shelf components) selection process is difficult due to the huge number of existing COTS components. Moreover, the price of a mistake is great due to the complex nature of information systems. In this paper an analysis of different COTS component selection methodologies is presented. Based on this, the ontology for supporting COTS component selection processes is proposed. In order to achieve a high level of practicality on different levels of decision making, the ontology is implemented in Protege software.

Ontology-Based Approaches to Big Data Analytics

The access to relevant information is one of the determining factors which directly influences on decision-making processes. Huge amounts of data have been accumulated by entities from large variety of sources in many different formats. Due to large amounts of information and continuous processes of generation of new parts, it is necessary to ensure the most effective way of information or data extraction and analysis. The Web of Data provides great opportunities for ontology-based services. The combination of ontology-based approaches and Big Data may help in solving some problems related to extraction of meaningful information from various sources. This paper presents the selected ontology-based approaches to Big Data analytics as well as a proposal of a procedure for ontology-based knowledge discovery.

Knowledge-Based Approach to Question Answering System Selection

A growth of data published on the Web is still observed. Keyword-based search, used by most search engines, is a common way of information retrieval on the Web. Subsequently, keyword-based search may provide a huge amount of retrieved valueless information. This problem can be solved by Question Answering System (QAS, QA system). One of the challenging tasks for available QA systems is to understand the natural language questions correctly and deduce the precise meaning to retrieve accurate responses. A significant role of QA and an increasing number of them may cause a problem with selection the most suitable QA system. The general aim of this paper is to provide knowledge-based approach to QA system selection. It should ensure knowledge systematization and help users to find a proper solution that meets their needs.

A Framework for Analysis of Ontology-Based Data Access

In last decade the terms related to Semantic Web become significant elements in the efficient way of information retrieval, processing and supporting availability of machine readable data. An ontology offers a wide spectrum of its application for data access. Ontology-Based Data Access is regarded as a key ingredient for the new generation of information systems, especially for Semantic Web applications that involve large amounts of data. OBDA system uses an ontology as a conceptual schema of the subject domain, and as a basis of the user interface for SQL database systems. This paper presents the complex overview of OBDA systems and a framework for analysis of selected tools for OBDA system creation.

Knowledge-Based Approach to COTS Software Selection Processes

The process of COTS (Commercial Off-The-Shelf) software selection is difficult due to the large number of existing COTS components. A complexity of COTS selection processes has great impact on the COTS method development, (information tools and frameworks in consequence). The main problem is how to use it on a given decision problem, and which suits the best to COTS component selection processes. In this paper an analysis of selected COTS frameworks and information tools supporting COTS component selection processes is proposed. It is a basis for ontologies construction using OWL (Ontology Web Language) standard. The two separated COTS ontologies are presented in this paper: ontology for frameworks and ontology for information tools supporting COTS software selection processes. The general aim of this is to provide the knowledge-based approach to COTS software selection processes.

Knowledge systematization for ontology learning methods

Abstract The need for interoperable semantics in modern information systems forces to develop more and more intelligent solutions. The increasing demand for these solutions, the explosion of various types of information and the technological development pose new challenges and requirements. Ontologies are often viewed as the answer to this need. The connections between ontologies and Semantic Web become a very promising area. The Semantic Web’s success is dependent on the quality of its underline ontologies, whereas ontologies provide a shared and a common understanding of a domain enabling communication between people and heterogeneous and distributed systems. However, key issue helps ontologies to power the Semantic Web have made ontology learning from various data sources a very auspicious field of research. It aims at semi-automatically or automatically building ontologies from given data sources with a limited human exert. A huge number of available approaches for ontology learning and the prominent differences between them cause the necessity of knowledge systematization for this domain. The paper yields the author’s proposal of ontological elaboration for methods for ontology learning and their features, providing formal, practical and technological guidance to knowledge management based approach to methods supporting ontology learning.

Towards Knowledge Handling in Ontology-Based Information Extraction Systems

Abstract Ontologies proved to be efficient and powerful tools for gathering and sharing knowledge, providing explicit specifications of conceptualizations. However, the proper ontology construction processes and their updating of various data sources, require a huge effort and well-adjusted mechanisms to their extraction, positioning and sharing. In this context, the application of a proper Ontology-Based Information Extraction (OBIE) system may help in solving these problems. The paper is a successful attempt to purvey state-of-the-art of selected OBIE systems, followed by the process of taxonomy construction and aftermath knowledge systematization of particular OBIE approaches.