Search Results - (( course evaluation tree algorithm ) OR ( user identification mining algorithm ))*

An efficient fuzzy clustering algorithm for mining user session clusters on web log data by Mallik, M. A., Zulkurnain, Nurul Fariza

“…This paper proposes an efficient Fuzzy Clustering algorithm for mining client session clusters from web access log information to find the groups of client profiles. …”
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A prototype for context identification of scientific papers via agent-based text mining by Mahmoud M.A., Ahmad M.S.

Context identification of scientific papers via agent-based model for text mining (ABM-TM) by Mahmoud M.A., Ahmad M.S., Yusoff M.Z.M., Mustapha A.

“…In this paper, we propose an agent-based text mining algorithm to extract potential context of papers published in the WWW. …”

Big Data Mining Using K-Means and DBSCAN Clustering Techniques by Fawzia Omer, A., Mohammed, H.A., Awadallah, M.A., Khan, Z., Abrar, S.U., Shah, M.D.

“…Therefore, this paper aims to analyze and cluster the log file data to get useful information that helps understand the users' behavior. A variety of data mining techniques were used to address the problem; three steps of data pre-processing were applied, namely the cleaning of data, the identification of users, and the identification of sessions. …”
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An analysis of text mining factors enhancing the identification of relevant studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

“…In this paper, we analyze the literature and identify the text mining factors that influence the identification of relevant studies. …”

A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

“…Secondly, a modified πRKM algorithm is proposed to partition the user session data. …”
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Dominance analyses reduction in skyline query processing over data stream with data mining technique by Ahmed Mohamud, Mudathir, Ibrahim, Hamidah, Sidi, Fatimah, Mohd Rum, Siti Nurulain

“…DAR employs the Apriori algorithm, one of the most prevalent data mining algorithms, to identify the frequently occurring dominance analyses. …”
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A Machine Learning Classification Application to Identify Inefficient Novice Programmers by Khan I., Al-Mamari A., Al-Abdulsalam B., Al-Abdulsalam F., Al-Khansuri M., Iqbal Malik S., Ahmad A.R.

Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

Context aware app recommendation using email semantic analysis by Tang, Zi Cong

“…The recommendation system is planned to develop by using data mining and machine learning. The email content as the raw data and sent to the test mining to perform text classification and category the data into differen t categories. …”
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An artificial intelligence approach to monitor student performance and devise preventive measures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…We developed a set of prediction models with distinct machine learning algorithms. Decision tree triumph over other models and thus is further transformed into easily explicable format. …”

Polycystic Ovary Syndrome (PCOS) prediction system using PSO-SVM / Lukman Hakim Shaufee, Hamidah Jantan and Ummu Fatihah Mohd Bahrin by Shaufee, Lukman Hakim

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Sentiment-analysis to detect early depressive symptom in Bangla language from social media: a review study by Hassan, Md. Hasibul, Kamaruddin, Azrina, Azmi Murad, Masrah Azrifah

“…The review shows that the mostly used method in Sentiment-analysis is Machine Learning in the field of Opinion-mining. Furthermore, we have identified another variable that can be included to improve the existing algorithm.…”
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A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…Educational Data Mining tools, specifically Machine learning classifiers, appear supportive to develop prediction models which forecast students� final outcome in a course. This research evaluates the effectiveness of machine learning classifiers to monitor students� academic progress and informs the instructor about the students at the risk of producing unsatisfactory final result in a course. …”

Multi-modality ontology semantic image retrieval with user interaction model / Mohd Suffian Sulaiman by Sulaiman, Mohd Suffian

“…To realise this approach, the semantic image retrieval prototype is developed based on the existing foundation algorithm and customised to provide the ability for user engagement in order to enhance the retrieval performance. …”
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Analytical method for forensic investigation of social networking applications on smartphones by Dezfouli, Farhood Norouzizadeh

“…Mobile devices are a gold mine of evidences for forensic investigators as they store valuable social networking data. …”
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An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

“…According to the research, 52% of students who sign up for a course would never read the course materials. Furthermore, throughout the course of five years, the dropout rate reached a stunning 96%. …”
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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

“…Particularly, the decision tree is identified as the most accurate predictive model, having a 0.60 accuracy value. …”
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DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi by Azmi, Muhammad Haziq

“…The project will implement automated detection and disease management recommendation algorithms while evaluating the functionality and usability of the designed application. …”
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Leveraging data lake architecture for predicting academic student performance by Abdul Rahim, Shameen Aina, Sidi, Fatimah, Affendey, Lilly Suriani, Ishak, Iskandar, Nurlankyzy, Appak Yessirkep

“…In addition to forecasting the student performance, appropriate machine learning algorithms such as Support Vector Classifier, Naive Bayes, and Decision Trees are used to build prediction models by using the data lake's scalability and parallel processing capabilities. …”
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