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লার্নিং অ্যানালিটিক্স×ক্রমিক বিন্যাস খনন (Sequential Pattern Mining)×
ক্ষেত্রশিক্ষা বিশ্লেষণযন্ত্র শিখন
পরিবারProcess / pipelineMachine learning
উদ্ভবের বছর20111995
প্রবর্তকGeorge Siemens & Phil LongRakesh Agrawal & Ramakrishnan Srikant
ধরনdata-driven educational process pipelineUnsupervised pattern discovery
মৌলিক উৎসSiemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40. link ↗Agrawal, R., & Srikant, R. (1995). Mining sequential patterns. IEEE International Conference on Data Engineering (ICDE), 3–14. DOI ↗
অপর নামEducational Data Mining, Academic Analytics, Learning Data Analytics, Öğrenme AnalitiğiSequence Pattern Mining, Sequential Data Mining, Temporal Pattern Mining, Ardışık Örüntü Madenciliği
সম্পর্কিত33
সারসংক্ষেপLearning Analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, with the purpose of understanding and optimizing learning and the environments in which it occurs. Formally introduced by George Siemens and Phil Long in 2011, the approach draws on data generated in digital learning environments to provide educators, institutions, and learners with evidence-based feedback for improving educational outcomes.Sequential Pattern Mining discovers ordered patterns that recur across multiple event sequences in a database. Introduced by Agrawal and Srikant in 1995, it extends association-rule mining to time-ordered transactions. A pattern is frequent when it appears as an ordered subsequence in at least a user-specified fraction of all sequences. The method is widely applied wherever the order of events carries meaning, such as customer purchase histories, clickstream logs, electronic health records, and DNA sequence analysis.
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ScholarGateপদ্ধতির তুলনা করুন: Learning Analytics · Sequential Pattern Mining. 2026-06-15 তারিখে সংগৃহীত, উৎস: https://scholargate.app/bn/compare