Google's PageRank algorithm for ranking nodes in general networks

Author(s):  
Joost Berkhout
Author(s):  
Sheng Zhang ◽  
Qi Luo ◽  
Yukun Feng ◽  
Ke Ding ◽  
Daniela Gifu ◽  
...  

Background: As a known key phrase extraction algorithm, TextRank is an analogue of PageRank algorithm, which relied heavily on the statistics of term frequency in the manner of co-occurrence analysis. Objective: The frequency-based characteristic made it a neck-bottle for performance enhancement, and various improved TextRank algorithms were proposed in the recent years. Most of improvements incorporated semantic information into key phrase extraction algorithm and achieved improvement. Method: In this research, taking both syntactic and semantic information into consideration, we integrated syntactic tree algorithm and word embedding and put forward an algorithm of Word Embedding and Syntactic Information Algorithm (WESIA), which improved the accuracy of the TextRank algorithm. Results: By applying our method on a self-made test set and a public test set, the result implied that the proposed unsupervised key phrase extraction algorithm outperformed the other algorithms to some extent.


NeuroSci ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 75-94
Author(s):  
Kulpreet Cheema ◽  
William E. Hodgetts ◽  
Jacqueline Cummine

Much work has been done to characterize domain-specific brain networks associated with reading, but very little work has been done with respect to spelling. Our aim was to characterize domain-specific spelling networks (SpNs) and domain-general resting state networks (RSNs) in adults with and without literacy impairments. Skilled and impaired adults were recruited from the University of Alberta. Participants completed three conditions of an in-scanner spelling task called a letter probe task (LPT). We found highly connected SpNs for both groups of individuals, albeit comparatively more connections for skilled (50) vs. impaired (43) readers. Notably, the SpNs did not correlate with spelling behaviour for either group. We also found relationships between SpNs and RSNs for both groups of individuals, this time with comparatively fewer connections for skilled (36) vs. impaired (53) readers. Finally, the RSNs did predict spelling performance in a limited manner for the skilled readers. These results advance our understanding of brain networks associated with spelling and add to the growing body of literature that describes the important and intricate connections between domain-specific networks and domain-general networks (i.e., resting states) in individuals with and without developmental disorders.


2021 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Chao Zhang ◽  
Huan Cao ◽  
Yun-Feng Huang ◽  
Bi-Heng Liu ◽  
Chuan-Feng Li ◽  
...  

2021 ◽  
Vol 11 (2) ◽  
pp. 25
Author(s):  
Evelina Forno ◽  
Alessandro Salvato ◽  
Enrico Macii ◽  
Gianvito Urgese

SpiNNaker is a neuromorphic hardware platform, especially designed for the simulation of Spiking Neural Networks (SNNs). To this end, the platform features massively parallel computation and an efficient communication infrastructure based on the transmission of small packets. The effectiveness of SpiNNaker in the parallel execution of the PageRank (PR) algorithm has been tested by the realization of a custom SNN implementation. In this work, we propose a PageRank implementation fully realized with the MPI programming paradigm ported to the SpiNNaker platform. We compare the scalability of the proposed program with the equivalent SNN implementation, and we leverage the characteristics of the PageRank algorithm to benchmark our implementation of MPI on SpiNNaker when faced with massive communication requirements. Experimental results show that the algorithm exhibits favorable scaling for a mid-sized execution context, while highlighting that the performance of MPI-PageRank on SpiNNaker is bounded by memory size and speed limitations on the current version of the hardware.


2020 ◽  
Vol 12 (8) ◽  
pp. 3457 ◽  
Author(s):  
Ruoxin Zhu ◽  
Diao Lin ◽  
Yujing Wang ◽  
Michael Jendryke ◽  
Rui Xin ◽  
...  

Regional development differences are a universal problem in the economic development process of countries around the world. In recent decades, China has experienced rapid urban development since the implementation of the reform and opening-up policy. However, development differs across regions, triggering the migration of laborers from underdeveloped areas to developed areas. The interaction between regional development differences and Spring Festival has formed the world’s largest cyclical migration phenomenon, Spring Festival travel. Studying the migration pattern from public spatiotemporal behavior can contribute to understanding the differences in regional development. This paper proposes a geospatial network analytical framework to quantitatively characterize the imbalance of urban/regional development based on Spring Festival travel from the perspectives of complex network science and geospatial science. Firstly, the urban development difference is explored based on the intercity population flow difference ratio, PageRank algorithm, and attractiveness index. Secondly, the community detection method and rich-club coefficient are applied to further observe the spatial interactions between cities. Finally, the regional importance index and attractiveness index are used to reveal the regional development imbalance. The methods and findings can be used for urban planning, poverty alleviation, and population studies.


2019 ◽  
Vol 957 ◽  
pp. 247-254
Author(s):  
Markus Moritz ◽  
Daniel Fuchs ◽  
Marian Gheorghe

In general, networks in companies or between companies play a significant role for monetary as well as non-monetary enhancement through cooperation. The aim is a positive effect for reducing innovation cycles, reducing costs and establishing a well-balanced time to market strategy. Besides open networks, where every actor is known, the existence of hidden networks, internal as well as external, have a substantial impact on strategic and operational activities meaning either a contribution or threat for the actors outside the hidden network. With the new models introduced in this publication, actors in various environments are able to identify hidden networks in order to be able to push contributions or eliminate risks leading from profit cuts to illegal knowledge transfer.


2002 ◽  
Vol 303 (5-6) ◽  
pp. 337-344 ◽  
Author(s):  
Zonghua Liu ◽  
Ying-Cheng Lai ◽  
Nong Ye ◽  
Partha Dasgupta

2021 ◽  
Author(s):  
JinWoo Kim ◽  
HyoungSun Na ◽  
Hee-Gook Jun ◽  
Jinhyun Ahn ◽  
Daesung Jun ◽  
...  

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