Search Results - (( course evaluation a algorithm ) OR ( text classification _ algorithm ))
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Comparative analysis of sensors and classification algorithms for land cover classification in Islamabad, Pakistan
Published 2025“…The satellite data with high-to-course spatial resolution data was utilized, and a comprehensive pre-processing workflow ensured high-quality imagery. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…In the process of summarizing relational data, a genetic algorithm is also applied and several feature scoring measures are evaluated in order to find the best set of relevant constructed features. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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Enhanced ontology-based text classification algorithm for structurally organized documents
Published 2015“…This research combines the ontology and text representation for classification by developing five algorithms. …”
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Using algorithmic taxonomy to evaluate lecturer workload
Published 2006“…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Text Extraction Algorithm for Web Text Classification
Published 2010“…This study provides a text extraction algorithm for web text classification. …”
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Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm
Published 2025“…University course timetabling problem (UCTP) is a scheduling problem that requires courses to be assigned to the limited time slots, classrooms, and lecturers, while adhering to a set of predefined constraints. …”
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
Published 2006“…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Comparative analysis of text classification algorithms for automated labelling of quranic verses
Published 2017“…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. We applied three text classification algorithms namely, k-Nearest Neighbour, Support Vector Machine, and Naïve Bayes in automating the labelling procedure. …”
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An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm
Published 2023“…However, the process of Quranic text classification is not without its challenges. …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Conference or Workshop Item -
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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
Published 2006“…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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