With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to d...With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.展开更多
We study the statistical properties of volatility of price fluctuation for the Hang-Seng index in the Hong Kong stock market, they are measured by locally averaging over a time window T, the absolute value of price ch...We study the statistical properties of volatility of price fluctuation for the Hang-Seng index in the Hong Kong stock market, they are measured by locally averaging over a time window T, the absolute value of price change over a short time interval Δt. The data include minute-by-minute records of the Hang-Seng index from 3 January 1994 to 28 May 1997. We find that the cumulative distribution of the volatility is consistent with the asymptotic power-law behaviour, characterized by the power exponent μ= 2.12 ± 0.04, different from that found in the previous studies as μ≈3. The volatility distribution remains the same asymptotic power-law behaviour for the time scales from T = 10 rain to T - 80 rain. Furthermore, we investigate the volatility correlations by using the power spectrum analysis and detrended fluctuation analysis. Both the methods show a long-range power-law decay with the exponent α=0.636±0.002.展开更多
We investigate a set of complex heart rate time series from healthy human in different behaviour states with the detrended fluctuation analysis and diffusion entropy （DE） method. It is proposed that the scaling prop...We investigate a set of complex heart rate time series from healthy human in different behaviour states with the detrended fluctuation analysis and diffusion entropy （DE） method. It is proposed that the scaling properties are influenced by behaviour states. The memory detected by DE exhibits an approximately same pattern after a detrending procedure. Both of them demonstrate the long-range strong correlations in heart rate. These findings may be helpful to understand the underlying dynamical evolution process in the heart rate control system, as well as to model the cardiac dynamic process.展开更多
We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulate...We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system： the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement （REM） sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.展开更多
The two-phase behaviour in financial markets actually means the bifurcation phenomenon, which represents the change of the conditional probability from an unimodal to a bimodal distribution. We investigate the bifurca...The two-phase behaviour in financial markets actually means the bifurcation phenomenon, which represents the change of the conditional probability from an unimodal to a bimodal distribution. We investigate the bifurcation phenomenon in Hang-Sang index. It is observed that the bifurcation phenomenon in financial index is not universal, but specific under certain conditions. For Hang-Sang index and randomly generated time series, the phenomenon just emerges when the power-law exponent of absolute increment distribution is between 1 and 2 with appropriate period. Simulations on a randomly generated time series suggest the bifurcation phenomenon itself is subject to the statistics of absolute increment, thus it may not be able to reflect essential financial behaviours. However, even under the same distribution of absolute increment, the range where bifurcation phenomenon occurs is fax different from real market to artificial data, which may reflect certain market information.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.T2293771)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.
基金Supported by the National Natural Science Foundation of China under Grant Nos 70471033, 10472116, 10532060, 10547004, 70571074, and 70571075.
文摘We study the statistical properties of volatility of price fluctuation for the Hang-Seng index in the Hong Kong stock market, they are measured by locally averaging over a time window T, the absolute value of price change over a short time interval Δt. The data include minute-by-minute records of the Hang-Seng index from 3 January 1994 to 28 May 1997. We find that the cumulative distribution of the volatility is consistent with the asymptotic power-law behaviour, characterized by the power exponent μ= 2.12 ± 0.04, different from that found in the previous studies as μ≈3. The volatility distribution remains the same asymptotic power-law behaviour for the time scales from T = 10 rain to T - 80 rain. Furthermore, we investigate the volatility correlations by using the power spectrum analysis and detrended fluctuation analysis. Both the methods show a long-range power-law decay with the exponent α=0.636±0.002.
基金Supported by the National Science Foundation of China under Grant Nos 70571075, 70571074 and 10635040, the Foundation for graduate students of University of Science and Technology of China under Grant No KD2006046, and the Foundation of Wang Kuan Cheng.
文摘We investigate a set of complex heart rate time series from healthy human in different behaviour states with the detrended fluctuation analysis and diffusion entropy （DE） method. It is proposed that the scaling properties are influenced by behaviour states. The memory detected by DE exhibits an approximately same pattern after a detrending procedure. Both of them demonstrate the long-range strong correlations in heart rate. These findings may be helpful to understand the underlying dynamical evolution process in the heart rate control system, as well as to model the cardiac dynamic process.
基金Supported by the National Science Foundation of China under Grant Nos 60471057 and 70571075, and the Foundation for Graduate Student of USTC under Grant No KD2006046.
文摘We study the dynamical properties of heart rate variability （HRV） in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system： the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement （REM） sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.
基金Supported by the National Natural Science Foundation of China under Grant Nos 70571075 and 10635040, and the National Basic Research Programme of China under Grant No 2006CB705500.
文摘The two-phase behaviour in financial markets actually means the bifurcation phenomenon, which represents the change of the conditional probability from an unimodal to a bimodal distribution. We investigate the bifurcation phenomenon in Hang-Sang index. It is observed that the bifurcation phenomenon in financial index is not universal, but specific under certain conditions. For Hang-Sang index and randomly generated time series, the phenomenon just emerges when the power-law exponent of absolute increment distribution is between 1 and 2 with appropriate period. Simulations on a randomly generated time series suggest the bifurcation phenomenon itself is subject to the statistics of absolute increment, thus it may not be able to reflect essential financial behaviours. However, even under the same distribution of absolute increment, the range where bifurcation phenomenon occurs is fax different from real market to artificial data, which may reflect certain market information.
