scholarly journals Weighted P-Rank Algorithm Based on aHeterogeneous Scholarly Network

2021 ◽  
Author(s):  
Jian Zhou ◽  
Lin Feng ◽  
Shenglan Liu ◽  
Jie Yang ◽  
Ning Cai
Keyword(s):  
Citation Network ◽  
Experimental Results ◽  
Scientific Article ◽  
Citation Networks ◽  
Competitive Performance ◽  
Personalized Pagerank ◽  
The Past ◽  
Ranking Algorithms ◽  
Public Datasets ◽  
Time Information

Abstract The evaluation of scientific article has always been a very challenging task because of the dynamicchange of citation networks. Over the past decades, plenty of studies have been conducted on thistopic. However, most of the current methods do not consider the link weightings between differentnetworks, which might lead to biased article ranking results. To tackle this issue, we develop aweighted P-Rank algorithm based on a heterogeneous scholarly network for article ranking evaluation.In this study, the corresponding link weightings in heterogeneous scholarly network can be updatedby calculating citation relevance, authors’ contribution, and journals’ impact. To further boost theperformance, we also employ the time information of each article as a personalized PageRank vectorto balance the bias to earlier publications in the dynamic citation network. The experiments areconducted on three public datasets (arXiv, Cora, and MAG). The experimental results demonstratedthat weighted P-Rank algorithm significantly outperforms other ranking algorithms on arXiv andMAG datasets, while it achieves competitive performance on Cora dataset. Under different networkconfiguration conditions, it can be found that the best ranking result can be obtained by jointlyutilizing all kinds of weighted information.

Longitudinal Analysis of Mechanism and Machine Theory: Geospatial Productivity, Journal Citation Networks, and Researcher Communities

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Dar-Zen Chen ◽  
Ya-Yun Lee
Keyword(s):  
Network Analysis ◽  
Longitudinal Analysis ◽  
Citation Network ◽  
The United States ◽  
Research Trends ◽  
Citation Networks ◽  
The Past ◽  
Research Communities ◽  
Citation Network Analysis ◽  
Machine Theory

This paper presents a longitudinal analysis through bibliometrics from three perspectives: geospatial analysis of research productivity, citation network analysis of journals, and top productive researchers with research communities. The purpose of these analyses is to detect the development and research trends of mechanism and machine theory (MMT) field. The results indicate that the productivity of MMT publications shows a growing trend. The United States (U.S.) has dominated MMT publications, but its ratio has dropped off approximately twenty percent in the past three decades, while China (CN) has rapidly grown in its quantity and ratio of MMT publications. The concentration of MMT publications among various countries has declined over time. Through citation network analysis, the relationships between journals in the MMT field are identified and their variations over periods are derived. The citations have been centered between five related journals and three core journals. Additionally, the evolution of research communities corresponding to the top 30 productive researchers and the distribution of the publications in each community among countries are identified.

METHOD FOR IDENTIFYING IMPORTANT NODES IN THE CITATION NETWORK OF SCIENTIFIC PUBLICATIONS

2021 ◽  
pp. 3-10
Author(s):  
I. G. Ol'gina
Keyword(s):  
Directed Graphs ◽  
Citation Network ◽  
Primary Sources ◽  
Centrality Measures ◽  
Scientific Article ◽  
Citation Networks ◽  
Scientific Publications ◽  
Node Importance ◽  
The Difference ◽  
Experimental Values

A mathematical method for selecting and ranking publications according to the degree of their compliance with the objectives of the research is developed and investigated. Bibliographic and abstract databases are used as primary sources of data on publications, which make it possible to track the citation of publications and identify the corresponding citation networks. The subject of the study is the citation networks of scientific publications. The mathematical model of citation networks is simple directed graphs whose vertices correspond to publications and whose arcs correspond to bibliographic references. The objectives of the research can be the preparation of a scientific article, writing a monograph or textbook, the design of a final qualifying work or dissertation, the replenishment of the library fund, etc. The research is carried out using the methods of Network Science. A method is proposed for determining the importance of the nodes of the citation network of scientific publications, taking into account the relevant measures of the centrality of the nodes and the profile of the research of publications. Relevant measures of centrality are indicators of the importance of nodes that are more appropriate than others and meet the search query for the selection of publications. The paper considers three profiles of the research of the citation network in order to rank publications. Since the citation network is oriented, the incoming and outgoing connections of the node are analyzed separately. The difference between the study profiles is that in one of them, only outgoing connections are taken into account in the centrality measures, in the other – incoming connections, and in the next, both are taken into account. An example of the application of the developed method of selection and ranking of scientific publications is given. The experimental values of the network node importance indicators were obtained on the basis of data on the citation of scientific publications in the RePEc bibliographic database.

Mining discriminative patches for script identification in natural scene images

2021 ◽  
Vol 40 (1) ◽  
pp. 551-563
Author(s):  
Liqiong Lu ◽  
Dong Wu ◽  
Ziwei Tang ◽  
Yaohua Yi ◽  
Faliang Huang
Keyword(s):  
Neural Networks ◽  
Experimental Results ◽  
The Other ◽  
Natural Scene ◽  
Fixed Size ◽  
Script Identification ◽  
Aspect Ratios ◽  
Novel Approach ◽  
Public Datasets ◽  
Natural Scene Images

This paper focuses on script identification in natural scene images. Traditional CNNs (Convolution Neural Networks) cannot solve this problem perfectly for two reasons: one is the arbitrary aspect ratios of scene images which bring much difficulty to traditional CNNs with a fixed size image as the input. And the other is that some scripts with minor differences are easily confused because they share a subset of characters with the same shapes. We propose a novel approach combing Score CNN, Attention CNN and patches. Attention CNN is utilized to determine whether a patch is a discriminative patch and calculate the contribution weight of the discriminative patch to script identification of the whole image. Score CNN uses a discriminative patch as input and predict the score of each script type. Firstly patches with the same size are extracted from the scene images. Secondly these patches are used as inputs to Score CNN and Attention CNN to train two patch-level classifiers. Finally, the results of multiple discriminative patches extracted from the same image via the above two classifiers are fused to obtain the script type of this image. Using patches with the same size as inputs to CNN can avoid the problems caused by arbitrary aspect ratios of scene images. The trained classifiers can mine discriminative patches to accurately identify some confusing scripts. The experimental results show the good performance of our approach on four public datasets.

scholarly journals Global publication trends and hotspots of molecular biomarkers in DILI from 1991 to 2020: A 30-year bibliometric analysis

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042110005
Author(s):  
Mingnan Cao ◽  
Li Wang ◽  
Lin Zhang ◽  
Jingli Duan
Keyword(s):  
Bibliometric Analysis ◽  
Research Collaboration ◽  
Citation Networks ◽  
Publication Trends ◽  
Drug Induced ◽  
Topic Area ◽  
The Past ◽  
Black Box Warnings ◽  
The Usa ◽  
Post Marketing

Drug-induced liver injury (DILI) is one of the common adverse drug reactions and the leading cause of drug development attritions, black box warnings, and post-marketing withdrawals. Current biomarkers are suboptimal in detecting DILI and predicting its outcome. This study aimed to quantitatively and qualitatively investigate the research trends on DILI biomarkers using bibliometric analysis. All relevant publications were extracted from the Web of Science database. An online analysis platform of literature metrology, bibliographic item co-occurrence matrix builder, and CiteSpace software were used to analyze the publication trends. CitNetExplorer was used to construct direct citation networks and VOSviewer was used to analyze the keywords and research hotspots. We found a total of 485 publications related to DILI biomarkers published from 1991 to 2020. Toxicological Sciences had been the most popular journal in this field over the past 30 years. The USA maintained a top position worldwide and provided a pivotal influence, followed by China. Among all the institutions, the University of Liverpool was regarded as a leader for research collaboration. Moreover, Professors Paul B. Watkins and Tsuyoshi Yokoi made great achievements in topic area. We analyzed the citation networks and keywords, therefore identified five and six research hotspot clusters, respectively. We considered the publication information regarding different countries/regions, organizations, authors, journals, et al. by summarizing the literature on DILI biomarkers over the past 30 years. Notably, the subject of DILI biomarkers is an active area of research. In addition, the investigation and discovery of novel promising biomarkers such as microRNAs, keratin18, and bile acids will be future developing hotspots.

Dynamical theory of neutron diffraction

1978 ◽  
Vol 56 (10) ◽  
pp. 1261-1288 ◽  
Author(s):  
V. F. Sears
Keyword(s):  
Neutron Diffraction ◽  
Theoretical Basis ◽  
Dynamical Theory ◽  
Experimental Results ◽  
Neutron Interferometry ◽  
New Techniques ◽  
The Past ◽  
Neutron Optics ◽  
Coherent Wave ◽  
Special Cases

We present a review of the dynamical theory of neutron diffraction by macroscopic bodies which provides the theoretical basis for the study of neutron optics. We consider both the theory of dispersion, in which it is shown that the coherent wave in the medium satisfies a macroscopic one-body Schrödinger equation, and the theory of reflection, refraction, and diffraction in which the above equation is solved for a number of special cases of interest. The theory is illustrated with the help of experimental results obtained over the past 10 years by a number of new techniques such as neutron gravity refractometry, Pendellösung interference, and neutron interferometry.

A Collaborative Filtering Recommendation Algorithm Incorporated with Life Cycle

2013 ◽  
Vol 765-767 ◽  
pp. 630-633 ◽  
Author(s):  
Chong Lin Zheng ◽  
Kuang Rong Hao ◽  
Yong Sheng Ding
Keyword(s):  
Life Cycle ◽  
Collaborative Filtering ◽  
Recommendation Systems ◽  
Experimental Results ◽  
User Interest ◽  
Recommendation Algorithm ◽  
Time Information ◽  
Successful Technology

Collaborative filtering recommendation algorithm is the most successful technology for recommendation systems. However, traditional collaborative filtering recommendation algorithm does not consider the change of time information. For this problem,this paper improve the algorithm with two new methods:Predict score incorporated with time information in order to reflect the user interest change; Recommend according to scores by adding the weight information determined by the item life cycle. Experimental results show that the proposed algorithm outperforms the traditional item in accuracy.

Research Paper Influence Measurement and Applications: A Machine-Learning-Based Approach

2014 ◽  
Vol 1049-1050 ◽  
pp. 2073-2078
Author(s):  
San Shan Du ◽  
Yue Chun Wu
Keyword(s):  
Machine Learning ◽  
Graph Theory ◽  
Academic Research ◽  
Meaningful Work ◽  
Citation Network ◽  
Citation Networks ◽  
Research Publication ◽  
American Airline ◽  
Airline Network ◽  
Influence Measurement

Measuring the influence of academic research publication is an meaningful work in academe. In this paper, the co-author and the citation networks are built to calculate the influence of a researcher and a paper in the way of networks separately with the discussion of further applications. At the beginning, the co-author network is built to determine the influence of co-authors. Then, based on the citations among the papers in the database, we build up the citation network with the help of graph theory. Thirdly, the method is implemented with the application of American Airline network analysis. As the final, the analysis of strengths and weaknesses is conducted.

scholarly journals The Place Of Karakalpak Ethnoculture In The Integration Of Society

2021 ◽  
Vol 03 (04) ◽  
pp. 676-688
Author(s):  
Halima Kadirova ◽  
Keyword(s):  
National Identity ◽  
Cultural Identity ◽  
Scientific Article ◽  
Social Changes ◽  
Next Generation ◽  
Way Of Life ◽  
The Past ◽  
Global Space ◽  
The People

This scientific article highlights the place and role of the Karakalpak ethnic culture in the development and preservation of the identity of the people. The authors analyze the culture and life of the modern Karakalpak family, which inherits to the next generation the traditional way of life associated with national holidays and traditions, dastans performed by Karakalpak bakhshi (singers), legends and legends of the past, told by the older generation. The article argues that social changes in the global space contribute to the emergence of certain changes in the content of cultural identity, language, art, spiritual categories, which are elements of the basis of the national identity of each nation and various ethno-regional units, which further strengthens the study of this issue under the influence of the process of globalization.

scholarly journals Multi-Task Self-Supervised Learning for Disfluency Detection

2020 ◽  
Vol 34 (05) ◽  
pp. 9193-9200
Author(s):  
Shaolei Wang ◽  
Wangxiang Che ◽  
Qi Liu ◽  
Pengda Qin ◽  
Ting Liu ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Large Scale ◽  
Experimental Results ◽  
Training Data ◽  
Competitive Performance ◽  
Test Set ◽  
Full Dataset ◽  
Sentence Classification ◽  
Trained Network

Most existing approaches to disfluency detection heavily rely on human-annotated data, which is expensive to obtain in practice. To tackle the training data bottleneck, we investigate methods for combining multiple self-supervised tasks-i.e., supervised tasks where data can be collected without manual labeling. First, we construct large-scale pseudo training data by randomly adding or deleting words from unlabeled news data, and propose two self-supervised pre-training tasks: (i) tagging task to detect the added noisy words. (ii) sentence classification to distinguish original sentences from grammatically-incorrect sentences. We then combine these two tasks to jointly train a network. The pre-trained network is then fine-tuned using human-annotated disfluency detection training data. Experimental results on the commonly used English Switchboard test set show that our approach can achieve competitive performance compared to the previous systems (trained using the full dataset) by using less than 1% (1000 sentences) of the training data. Our method trained on the full dataset significantly outperforms previous methods, reducing the error by 21% on English Switchboard.

scholarly journals 10 common mistakes in writing a scientific article

2019 ◽  
Vol 9 ◽  
pp. 4-6
Author(s):  
Carlos Flores-Mir
Keyword(s):  
Associate Editor ◽  
Scientific Article ◽  
Manuscript Submission ◽  
The Past

Over the past 15 years, I have been involved in different roles as author of orthodontic and non-orthodontic manuscripts, reviewer of orthodontically related submissions and assistant/associate editor of different orthodontic journals. Over that span, I have committed multiple mistakes both while writing a manuscript and while critically appraising one. I hope these few timbits* would help you strengthen any future manuscript submission you may consider working on. I have identified 10 common mistakes that I have observed while preparing/reading scientific articles. The list is not ordered according to importance but following the template of a typical scientific article.

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