Search Results - (( model evaluation case 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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Feature extraction from natural language to aid requirements reuse in software product lines engineering / Noor Hasrina Bakar by Noor Hasrina, Bakar

“…FENL consists of four main phases: Accessing Requirements, Terms Extraction, Feature Identification and Formation of Feature Model. The proposed model is demonstrated through lab experiment and online software reviews are used as the input. …”
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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.

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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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Identification of non-linear dynamic systems using fuzzy system with constrained membership functions by Yaakob, Mohd. Shafiek

“…In this study, the identification performance of the SFS trained by the back-propagation (BP) algorithm forms the basis of comparison when evaluations were made on the performance of the newly proposed CFS models. …”
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Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method by Mohammed, Rawia Tahrir, Yaakob, Razali, Mohd Sharef, Nurfadhlina, Abdullah, Rusli

“…Lastly, the most suitable criteria outcomes are formulated in the unifying model and evaluate by experts to verify the appropriateness and suitability of the model in assessing the MaOO algorithms fairly and effectively.…”
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Deep learning in public health: Comparative predictive models for COVID-19 case forecasting by Muhammad Usman Tariq, Muhammad Usman Tariq, Ismail, Shuhaida

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. …”
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Modelling and environmental assessment of heterogeneous catalysis biodiesel process using war algorithm by As Eleyana, Ali

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Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq by Al‑Aqeeli, Yousif H., Lee, Teang Shui, Abd Aziz, Samsuzana

“…The performances of these two algorithms were evaluated through the comparison of their optimal values of annual hydropower generation during the 20 scenarios of operating. …”
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Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

“…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala's, Acir's, Liu's, and Dingle's peak models. …”
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Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

“…The proposed algorithm is characterized by a search model namely the sensitive search model, where the exploitation-exploration is adaptively balanced. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

“…Case study evaluation was conducted based on three industrial open source case studies in order to evaluate empirically the significant of the performance of the proposed method. …”
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Dual optimization approach in discrete Hopfield neural network by Guo, Yueling, Zamri, Nur Ezlin, Mohd Kasihmuddin, Mohd Shareduwan, Alway, Alyaa, Mansor, Mohd. Asyraf, Li, Jia, Zhang, Qianhong

“…Quantitative evaluations show that the proposed model successfully enhances the optimization of both phases, ranking first compared to 10 recent algorithms for all metrics. …”
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