Extension of Direct Citation Model Using In-Text Citations

Citations based relevant research paper recommendations can be generated primarily with the assistance of three citation models:(1)Bibliographic Coupling,(2)Co-Citation,and(3)Direct Citations.Millions of new scholarly articles are published every year.This flux of scientific information has made it a challenging task to devise techniques that could help researchers to find the most relevant research papers for the paper at hand.In this study,we have deployed an in-text citation analysis that extends the Direct Citation Model to discover the nature of the relationship degree-ofrelevancy among scientific papers.For this purpose,the relationship between citing and cited articles is categorized into three categories:weak,medium,and strong.As an experiment,around 5,000 research papers were crawled from the CiteSeerX.These research papers were parsed for the identification of in-text citation frequencies.Subsequently,0.1 million references of those articles were extracted,and their in-text citation frequencies were computed.A comprehensive benchmark dataset was established based on the user study.Afterwards,the results were validated with the help of Least Square Approximation by Quadratic Polynomial method.It was found that degreeof-relevancy between scientific papers is a quadratic increasing/decreasing polynomial with respect to-increase/decrease in the in-text citation frequencies of a cited article.Furthermore,the results of the proposed model were compared with state-of-the-art techniques by utilizing a well-known measure,known as the normalized Discount Cumulative Gain(nDCG).The proposed method received an nDCG score of 0.89,whereas the state-of-the-art models such as the Content,Bibliographic-coupling,and Metadata-based Models were able to acquire the nDCG values of 0.65,0.54,and 0.51 respectively.These results indicate that the proposed mechanism may be applied in future information retrieval systems for better results.

Research progress of heat stroke during 1989–2019: A bibliometric analysis

Background: Heat stroke(HS) is an acute physical disorder that is associated with a high risk of organ dysfunction and even death. HS patients are usually treated symptomatically and conservatively;however, there remains a lack of specific and effective drugs in clinical practice. An analysis of publication contributions from institutions, journals and authors in different countries/regions was used to study research progress and trends regarding HS.Methods: We extracted all relevant publications on HS between 1989 and 2019 from Web of Science. Using the Statistical Package for Social Science(SPSS, version 24) and the software GraphPad Prism 8, graphs were generated and statistical analyses were performed, while VOSviewer software was employed to visualize the research trends in HS from the perspectives of co-occurring keywords.Results: As of April 14, 2020, we identified 1443 publications with a citation frequency of 5216. The United States accounted for the largest number of publications(36.2%) and the highest number of citations(14,410), as well as the highest H-index at 74. Although the sum of publications from China ranked second, there was a contradiction between the quantity and quality of publications. Furthermore, Medicine & Science in Sports & Exercise published the most papers related to HS, with Lin MT publishing the most papers in this field(112), while the review by Knochel JP received the highest citation frequency at 969. The keyword heat-stress appeared most recently, with an average appearing year of 2015.5. In the clinical research cluster, exertional heat-stroke was determined to be the hotspot, while ambient-temperature and heat waves were the new trends in the epidemiological research cluster.Conclusions: Corresponding to this important field, while the contributions of the publications from the United States were significant, the mismatch between the quantity and quality of publications from China must be examined. Moreover, it is hypothesized that clinical and epidemiological studies may become hotspots in the near future.

An ethnobotanical study of medicinal plants in Güce district,north-eastern Turkey

This study aims to identify medicinal plants traditionally used to treat diseases by local people living in Güce district,north-eastern Turkey.The study was carried out between 2018 and 2021 using a two-part semi-structured,open-ended questionnaire with 165 local people.Data were analysed using use-report,frequency of citation,and informant consensus factor.Informants identified 128 vascular medicinal plant taxa belonging to 54 families and 106 genera.The most common plant taxa belong to Rosaceae(16 taxa/12.5%),Asteraceae(12 taxa/9.4%),and Lamiaceae(9 taxa/7%)families.The most frequently used preparation method reported was decoction(39.8%);the most commonly utilized plant parts were leaves(40.3%).Statistical analysis reveals that women in Güce district(df?163,p?0.043<0.05)possess the most traditional knowledge.The highest frequency of citation(61)and use report(92)were recorded for Tilia rubra subsp.caucasica,and the highest informant consensus factors were cited for respiratory system disorders(0.86),digestive system disorders(0.73),and skin disorders(0.71).This study reported nine plant taxa as medicinal plants for the first time,and documented a total of 293 new therapeutic uses.However,the study indicates that the transfer of traditional knowledge to future generations is limited(F?3.355,p?0.020).Action should be taken as soon as possible to preserve existing traditional knowledge and to ensure its transfer to future generations.