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Huafeng Xie

Publications and source records attributed to Huafeng Xie.

3 recordsLinked to original sources

Ranking Scientific Publications Using a Simple Model of Network Traffic

To account for strong aging characteristics of citation networks, we modify Google's PageRank algorithm by initially distributing random surfers exponentially with age, in favor of more recent publications. The output of this algorithm, which we call CiteRank, is interpreted as approximate traffic to individual publications in a simple model of how researchers find new information. We develop an analytical understanding of traffic flow in terms of an RPA-like model and optimize parameters of our algorithm to achieve the best performance. The results are compared for two rather different citation networks: all American Physical Society publications and the set of high-energy physics theory (hep-th) preprints. Despite major differences between these two networks, we find that their optimal parameters for the CiteRank algorithm are remarkably similar.

physics.soc-ph

Optimal ranking in networks with community structure

The World-Wide Web (WWW) is characterized by a strong community structure in which groups of webpages (e.g. those devoted to a common topic or belonging to the same organization) are densely interconnected by hyperlinks. We study how such network architecture affects the average Google rank of individual communities. Using a mean-field approximation, we quantify how the average Google rank of community webpages depends on the degree to which it is isolated from the rest of the world in both incoming and outgoing directions, and $α$ -- the only intrinsic parameter of Google's PageRank algorithm. Based on this expression we introduce a concept of a web-community being decoupled or conversely coupled to the rest of the network. We proceed with empirical study of several internal web-communities within two US universities. The predictions of our mean-field treatment were qualitatively verified in those real-life networks. Furthermore, the value $α=0.15$ used by Google seems to be optimized for the degree of isolation of communities as they exist in the actual WWW.

physics.soc-ph

Effects of Community Structure on Search and Ranking in Information Network

The World-Wide Web (WWW) is characterized by a strong community structure in which communities of webpages (e.g. those sharing a common keyword) are densely interconnected by hyperlinks. We study how such network architecture affects the average Google ranking of individual webpages in the comunity. It is shown that the Google rank of community webpages could either increase or decrease with the density of inter-community links depending on the exact balance between average in- and out-degrees in the community. The magnitude of this effect is described by a simple analytical formula and subsequently verified by numerical simulations of random scale-free networks with a desired level of the community structure. A new algorithm allowing for generation of such networks is proposed and studied. The number of inter-community links in such networks is controlled by a temperature-like parameter with the strongest community structure realized in "low-temperature" networks.

cond-mat.other