Title :
Extraction of Key Papers Based on the PageRank Algorithm Using Variance Values of Cited Literature as Weighting
Author_Institution :
Center for Educ. & Res., Ochanomizu Univ., Tokyo, Japan
Abstract :
Even though citation analysis are a recent popular study trend in the field of academic landscape achieving the stage of automated clustering, the reality is that experts manually analyze semantic attachments to identify the type of group for each cluster. Therefore, we attempt to achieve an automated extraction of key literature of each cluster in the report by setting automated interpretation of each cluster as the final purpose of the study.
Keywords :
citation analysis; data mining; information retrieval; pattern clustering; text analysis; PageRank algorithm; automated interpretation; automatic clustering; automatic key literature extraction; citation analysis; cited literature; data mining; group type identification; key paper extraction; semantic attachments; variance values; Bibliometrics; Clustering algorithms; Data mining; Databases; Histograms; Standards; Visualization; Big Data; Clustering; Data Mining;
Conference_Titel :
Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-4873-7
DOI :
10.1109/CIT.2012.114
