Opinion Mining In Big Data: Trend of Thinking for Big Data Era (Published)
This ear with the rapidly growing of internet and network using there are a huge data that have been introduced, Big Data are now on the double expanding rabidly in all domains, including opinion and sentiment analysis, for there are many social media and other websites that offer chances to provide the visitors and customers to post their opinion which usually contains valuable information that could be helpfully for several issues. And there are different methods and techniques that proposed to face this huge data and the big social data to make it more beneficial for several fields. This Paper introduces the big data and the most common it is usage and challenge, and it also investigate the sentiment analysis and it is common techniques and thinking about it is futures. This paper also thinking about the future of big data and opinion mining is clearly discussed and thinking about the future of big data and opinion mining. And the paper will discuss the challenges that facing the big data and opinion mining.
Keywords: Big Data, Data mining, Social media, opinion mining
A classification model for water quality analysis using decision tree (Published)
A classification algorithm is used to assign predefined classes to test instances for evaluation) or future instances to an application). This study presents a Classification model using decision tree for the purpose of analyzing water quality data from different counties in Kenya. The water quality is very important in ensuring citizens get to drink clean water. Application of decision tree as a data mining method to predict clean water based on the water quality parameters can ease the work of the laboratory technologist by predicting which water samples should proceed to the next step of analysis. The secondary data from Kenya Water institute was used for creation of this model. The data model was implemented in WEKA software. Classification using decision tree was applied to classify /predict the clean and not clean water. The analysis of water Alkalinity,pH level and conductivity can play a major role in assessing water quality. Five decision tree classifiers which are J48, LMT, Random forest, Hoeffding tree and Decision Stump were used to build the model and the accuracy compared. J48 decision tree had the highest accuracy of 94% with Decision Stump having the lowest accuracy of 83%.
Keywords: Data mining, Decision Tree, Water Quality, Weka Tool, classification model
Using Data Mining Techniques to Identify the Causes of Deaths in Al-Gedaref Hospital (Published)
Data mining technology extensively used in managing relationship through a variety of approaches. There are many tools and methods for analyzing mortality data. The mining technology is one of these tools. The research aims to illustrate the concept of data mining and causes of deaths in Gedaref hospital. The methodology of data mining which used in deaths files is used to integrate two algorithms which are (clustering and classification) to help Gedaref state hospital on prediction and decision making. The study also aims to indicate the level of the interest in the exploration areas and the components of the structure of the application of exploration concepts and tools. One can concluded that the large proportion of deaths is caused by Malaria especially between male’s students and employees in early ages 32 year who live in Kassab village in Gedaref. We also recommended that the hospital administration have to provide training programs to workers
Keywords: Cause of Death, Computer Application, Data mining, Database
NEURAL NETWORKS APPROACH FOR MONITORING AND SECURING THE E-GOVERNMENT INFORMATION SYSTEMS (Published)
Security must be addressed in the phase of planning and designing of e-government system. Management process is needed to assess security control, where management allows departments and agencies to maintain and measure the extent of data security depending on the mechanism of revealing the security weak points .Revealing the weak points is done by using a series of standards built on the application of machine learning methods specifically Using the Neural Networks Model, and intelligent data analysis. All these techniques are useful in monitoring and measuring the extent of the secured data and the provided services. The applied results on the data site of ”Cairo cleanliness and beautification authority for cleaning” in Egypt showed that measurement qualifications were adequate, proper ,preaching, and can be generalized. The proposed approach of monitoring is very comprehensive where it limits the risk of information security that affect organizations’ risk management decisions.
Keywords: Data mining, Government Cyber space, the Neural Networks Model