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• W2213307122 abstract "Text mining concerns discovering and extracting knowledge from unstructured data. It transforms textual data into a usable, intelligible format that facilitates classifying documents, finding explicit relationships or associations between documents, and clustering documents into categories. Given a collection of survey comments evaluating the civil engineering learning system, text mining technique is applied to discover and extract knowledge from the comments. This research focuses on the study of a systematic way to apply a software tool, SAS Enterprise Miner, to the survey data. The purpose is to categorize the comments into different groups in an attempt to identify “major” concerns from the users or students. Each group will be associated with a set of key terms. This is able to assist the evaluators of the learning system to obtain the ideas from those summarized terms without the need of going through a potentially huge amount of data." @default.
• W2213307122 created "2016-06-24" @default.
• W2213307122 creator A5077749414 @default.
• W2213307122 date "2010-01-01" @default.
• W2213307122 modified "2023-09-27" @default.
• W2213307122 title "A pilot study in an application of text mining to learning system evaluation" @default.
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• W2213307122 hasPublicationYear "2010" @default.
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