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Recent development in the field of Academic Landscape consists mainly in quotation network analysis. It is possible to sort tens of thousands of academic papers into clusters automatically by making full use of the various techniques that we describe in Section 2. However, it is not yet possible to automatically define the characteristics of each field identified by clustering as well as to automatically extract major papers in each field. Thus, We research the method to automatically identify major papers in each field recognized by clustering. Specifically, We examine the variance of years when a paper was quoted; then we apply the variance to the page rank algorithm to calculate the importance of a paper. We also aim to build up a hiangle map with a temporal axis based on the importance. Finally, We describe the constitution of this paper. Section 2 surveys the preceding studies of network analysis, clustering and bibliometrics that are element technologies to realize Academic Landscape. Section 3 describes the purpose of this study and proposed method. Furthermore, Section 4 refers to the result of experimental evaluation of the proposed method before the conclusion in Section 5.

Academic Landscape Based on Network Analysis Considering Analysis of Variation in the Years of Lucubration Publishing