Introduction Nowadays, there is a huge amount of data found in different web platforms worldwide, one of the most important data sources is the Wikipedia [1] which includes information about everything in our life. Semantic Web technology [2] became one of the most important techniques which used to increase the quality of data through the web be transforming the data format from unstructured data to structured data. Through this research we will focus on clarifying the rule of semantic web [3] in improving the quality of data using different mechanisms and we will show how to improve the performance of data by reducing the response time of querying this information through semantic web query language aided by big data tools. The rest of research will is organized as follow: Section 2 focuses on the literature review which may be similar to our methodology. Section 3 discusses our main proposed methodology for this research. Section 4 presents the analysis of the proposed architecture according to its implementation and the conducted results. Finally, section 5 concludes our paper and discusses the possible directions for future work. 2. Research Problem One of the main problems that faced Wikipedia is that it represents its information in un-structured format, which leads to quality problem according to the mismanagement of this information such as the difficulty of processing this information or query it. Also, through this research we will focus on another problem which relates to the huge size of Wikipedia data, however the sematic web technology help us to improve the quality of data but the problem still found when we talk about large amount of data which leads to another quality problem such as the performance and the response time of querying. 3. Research Objectives The main objective is how to get use of this huge amount of data and put it in a simple form to produce an accurate results using quality technique semantic technology. 4. Research Hypothesis The research wills discus certain hypotheses such as it, There is a significant relationship between improving the Total data quality management using the semantic technology. There is a significant relationship between improving the performance of data query using the semantic technology in big data environment.
Researchers in the quality assurance field used traditional techniques for increasing the organization income and take the most suitable decisions. Today they focus and search for a new intelligent techniques in order to enhance the quality of their decisions. This paper based on applying the most robust trend in computer science field which is data mining in the quality assurance field. The cases study which is discussed in this paper based on detecting and predicting the developed and developing countries based on the indicators. This paper uses three different artificial intelligent techniques namely; Artificial Neural Network (ANN), k-Nearest Neighbor (KNN), and Fuzzy k-Nearest Neighbor (FKNN). The main target of this paper is to merge between the last intelligent techniques applied in the computer science with the quality assurance approaches. The experimental result shows that proposed approaches in this paper achieved the highest accuracy score than the other comparative studies as indicates in the experimental result section.
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