DocumentCode :
2358298
Title :
The Application and Research of Text Mining in Relevance about Choosing Course and Research Project by Graduate Student
Author :
Wang, Qin ; Qu, Shou-Ning ; Dong, Caiyun ; Liu, Kui
Author_Institution :
Sch. of Inf. Sci. & Eng., Univ. of Jinan, Jinan, China
fYear :
2009
fDate :
25-27 Aug. 2009
Firstpage :
1469
Lastpage :
1472
Abstract :
At present, graduate students need choose some courses by themselves, which had some blindness. The paper put forward a suit of text mining algorithms based on association rule. The algorithms were used in studying relevance between choosing course and research project, which could provide some reference for graduate students. At first, the scheme of computing words´ relevant degree was put forward and the words´ relevant degree could be gotten. Then a similarity calculation algorithm based on parallel architecture was brought forward, and the words´ relevant degree was used in similarity calculation algorithm, the similarity between two documents could be gotten. Using digital library as experiment platform, a series of algorithms were used to mine the documents similarity between courses and research project, so the course sequence correlated with research project could finally be gotten. Experiment showed that the scheme had some reference and use value.
Keywords :
data mining; digital libraries; educational computing; educational courses; text analysis; association rule; digital library; graduate students; parallel architecture; research projects; similarity calculation algorithm; text mining algorithms; Association rules; Blindness; Clustering algorithms; Data mining; Databases; Educational institutions; Information science; Parallel architectures; Software libraries; Text mining; Association rules; Relevant; Text clustering; Text mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5209-5
Electronic_ISBN :
978-0-7695-3769-6
Type :
conf
DOI :
10.1109/NCM.2009.157
Filename :
5331341
Link To Document :
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