Adjustable Preferential Attachment Model On Citation Network And Its Application

Citation network is a network to build the citation relations between papers. The analysis on citation network is one of the key methods to review the history of science development, to evaluate and predict the value, the scale and the tendency of science development. Two important goals of the analysis are analyzing structural properties and modeling network evolution. Existing models have failed to simultaneously explain following structural properties of citation network: preferential attachment phenomena, node aging phenomena, scale-free, sleepy beauties phenomena and high clustering. This thesis proposes a model of evolving citation network which explains above properties, and applies the evolution rules of citation network indicated by this model to predict the development of citation networks. The main contributions are as follows:1. This thesis proposes Adjustable Preferential Attachment Model (APA Model) to describe citation network. Firstly this thesis proposes APA Model for the two major mechanisms of citation network, which are node aging mechanism and edge copying mechanism. The influence of the APA Model parameters of the above two mechanisms to network structure is studied through both analytical analysis and numerical simulation. The relationships between the two process of APA Model and the five structural properties of citation network are also analyzed. The analyzed relationships show that APA Model can describe citation network well and explain the structural properties, respectively.2. This thesis presents a parameter estimation method for APA Model to validate the ability of APA Model to rationally describe the real citation network. The consistency between the five structural properties of real citation networks and of simulated networks constructed according to the parameters estimated from real citation networks is analyzed, and the result shows APA Model can rationally describe the real citation network and simultaneously explain the structural properties of real citation network. The reason of the different parameters obtained from different real citation networks is also provided. The rational description of real citation network by APA Model can indicate the evolution rules of citation network. 3. Based on APA Model, this thesis proposes an algorithm to predict prospective hot research topics. According to the increasing rules of citations simultaneously indicated by APA Model, the probability to obtain new citations of one paper are predicted based on recent citations. Experimental results demonstrate that the new algorithm achieves higher prediction accuracy than other prediction algorithms. Through rank aggregation, it is confirmed that prospective hot research topics can be reliably predicted using only recent citation. Finally, the ranking of recent citations is integrated into a literature search engine with query expansion technology, the search engine can help the users obtain detailed research field and hot research topics of user-specified research field.