Ordered weighted logarithmic averaging distance-based pattern recognition for the recommendation of traditional Chinese medicine against COVID-19 under a complex environment

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuhe Fu ◽  
Chonghui Zhang ◽  
Yujuan Chen ◽  
Fengjuan Gu ◽  
Tomas Baležentis ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Recommendation System ◽  
Distance Measure ◽  
Uncertain Information ◽  
Content Type ◽  
Appropriate Treatment ◽  
Treatment Plans ◽  
Fuzzy Linguistic

PurposeThe proposed DHHFLOWLAD is used to design a recommendation system, which aims to provide the most appropriate treatment to the patient under a double hierarchy hesitant fuzzy linguistic environment.Design/methodology/approachBased on the ordered weighted distance measure and logarithmic aggregation, we first propose a double hierarchy hesitant fuzzy linguistic ordered weighted logarithmic averaging distance (DHHFLOWLAD) measure in this paper.FindingsA case study is presented to illustrate the practicability and efficiency of the proposed approach. The results show that the recommendation system can prioritize TCM treatment plans effectively. Moreover, it can cope with pattern recognition problems efficiently under uncertain information environments.Originality/valueAn expert system is proposed to combat COVID-19 that is an emerging infectious disease causing disruptions globally. Traditional Chinese medicine (TCM) has been proved to relieve symptoms, improve the cure rate, and reduce the death rate in clinical cases of COVID-19.

scholarly journals Research on healthy catering recommendation space

2020 ◽  
Vol 309 ◽  
pp. 03011
Author(s):  
Yongjie Deng ◽  
Yong Liu ◽  
Dongping Tang
Keyword(s):  
Health Status ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Questionnaire Survey ◽  
Recommendation System ◽  
Constitutional Theory ◽  
Theoretical Knowledge ◽  
Key Factors ◽  
Individual Preferences ◽  
Depth Study

This paper conducts an in-depth study on the catering recommendation space based on different situations. By consulting the literature, visiting relevant experts, condensing the theoretical knowledge of TCM (Traditional Chinese Medicine) constitutional dietotherapy theory, it has extracted some key factors that can be effectively utilized in catering theory. The variable framework of the situational catering recommendation system is preliminarily constructed. Also, it has designed a mixed catering recommendation space that combines TCM Constitutional Theory and user situation, which not only meets individual preferences but also improves the users’ sub-health status. Finally, through the questionnaire survey, the importance of each attribute in the eyes of consumers has been recognized; then this essay provides a guidance for the recommendation ranking method in the design of the catering recommendation system after making the cross-analysis.

Identifying health information needs of senior online communities users: a text mining approach

2020 ◽  
Vol 73 (1) ◽  
pp. 5-24
Author(s):  
Yuxing Qian ◽  
Wenxuan Gui
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Health Information ◽  
Online Communities ◽  
Western Medicine ◽  
Information Needs ◽  
Information Services ◽  
Health Issues ◽  
Medical Systems ◽  
Content Type

PurposeThe purpose of this study is to identify the health information needs of senior online communities (SOCs) users, which could provide a basis for improving senior health information services.Design/methodology/approachA total of 14,933 health-related posts in the two most popular senior online communities (Yinling and Keai) in China are crawled as a corpus. Based on the results of word frequency analysis, text classification is performed based on two aspects: medical systems (Western medicine and traditional Chinese medicine) and topics. The health information needs of SOCs users are revealed from the composition, growth trends and popularity of health information. Finally, some key points of senior health information services are discussed.FindingsThe health information needs of senior users can be divided into four types: coping with aging, dietary nutrition, physical exercise and mental health. These needs are comprehensive and involve a variety of health issues. Users are mainly concerned with physical health issues. In terms of medical systems, the number of Western medicine posts is relatively larger, whereas traditional Chinese medicine appears more in posts on coping with aging and physical exercise. The health information needs of SOCs users are in a stable status. Both the medical systems and topics could have an impact on the popularity of health information, but the number of posts is inconsistent with the level of popularity.Originality/valueThis study combines multiple perspectives to identify the health information needs of seniors in China with a comprehensive overview.

Comparision of Bupleurum scorzoneri folium Willd. Grouping from Different Habitats Based on Pattern Recognition with R Software

2011 ◽  
Vol 393-395 ◽  
pp. 1139-1142
Author(s):  
Wen Rui ◽  
Hong Yuan Chen ◽  
Yi Fan Feng ◽  
Zhong Feng Shi ◽  
Miao Miao Jiang
Keyword(s):  
Pattern Recognition ◽  
Chemical Composition ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Hierarchical Clustering ◽  
Chemical Data ◽  
R Software ◽  
Pattern Recognition Methods

Bupleurum scorzoneri folium Willd.(BSFW) is a traditional Chinese medicine which is widely distributed in China. To evaluate the quality of BSFW from different habitats, samples from 5 different areas in China were determined by UPLC/MS. The chemical data were dealed with hierarchical clustering, PCA, SPCA, PLSDA and SPLSDA using R software. The results show that these pattern recognition methods can fully reflect the chemical composition of different areas of BSFW, which make it possible to control the quality.

Diagnosing with Light

2019 ◽  
Vol 35 (3) ◽  
pp. 365-400
Author(s):  
Sally Ann Ness ◽  
Keyword(s):  
Pattern Recognition ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Diagnostic Technique ◽  
Evolutionary Stage ◽  
Linguistic Representation ◽  
Gradual Accumulation ◽  
Emissions Testing

Acupoint Biophoton Emissions Testing (ABET), an alternative diagnostic technique used by practitioners of Traditional Chinese Medicine, illustrates a case of non-linguistic Delome-level semiosis that is understood to form an interface between endosemiotic and linguistic semiotic levels of human (bio-)communication. Performed manually, the technique employs an array of Hypoiconic and Indexical Symbols that, when used in combination, enable practitioners to “listen in” and learn with biocommunicational processes, re-embodying them in a manner that renders them available to conscious recognition and linguistic representation. The Delome formations of the ABET technique afford the gradual accumulation and transformation of practitioner understanding through sign co-performances that achieve triadic relationality mediationally—prefiguring fully representational forms of learning. They demonstrate embodied capacities for pattern recognition, coordination, exploration, articulation, explication and self-governance that may have evolved in advance of representational sign formations, setting the evolutionary stage for them.

Mapping knowledge domains on Wikipedia: an author bibliographic coupling analysis of traditional Chinese medicine

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dangzhi Zhao ◽  
Andreas Strotmann
Keyword(s):  
Chinese Medicine ◽  
Herbal Medicine ◽  
Traditional Chinese Medicine ◽  
Bibliographic Coupling ◽  
Knowledge Domain ◽  
Coupling Analysis ◽  
Falun Gong ◽  
Content Type ◽  
Knowledge Domains ◽  
Lofty Goal

PurposeWikipedia has the lofty goal of compiling all human knowledge. The purpose of the present study is to map the structure of the Traditional Chinese Medicine (TCM) knowledge domain on Wikipedia, to identify patterns of knowledge representation on Wikipedia and to test the applicability of author bibliographic coupling analysis, an effective method for mapping knowledge domains represented in published scholarly documents, for Wikipedia data.Design/methodology/approachWe adapted and followed the well-established procedures and techniques for author bibliographic coupling analysis (ABCA). Instead of bibliographic data from a citation database, we used all articles on TCM downloaded from the English version of Wikipedia as our dataset. An author bibliographic coupling network was calculated and then factor analyzed using SPSS. Factor analysis results were visualized. Factors were labeled upon manual examination of articles that authors who load primarily in each factor have significantly contributed references to. Clear factors were interpreted as topics.FindingsSeven TCM topic areas are represented on Wikipedia, among which Acupuncture-related practices, Falun Gong and Herbal Medicine attracted the most significant contributors to TCM. Acupuncture and Qi Gong have the most connections to the TCM knowledge domain and also serve as bridges for other topics to connect to the domain. Herbal medicine is weakly linked to and non-herbal medicine is isolated from the rest of the TCM knowledge domain. It appears that specific topics are represented well on Wikipedia but their conceptual connections are not. ABCA is effective for mapping knowledge domains on Wikipedia but document-based bibliographic coupling analysis is not.Originality/valueGiven the prominent position of Wikipedia for both information users and for researchers on knowledge organization and information retrieval, it is important to study how well knowledge is represented and structured on Wikipedia. Such studies appear largely missing although studies from different perspectives both about Wikipedia and using Wikipedia as data are abundant. Author bibliographic coupling analysis is effective for mapping knowledge domains represented in published scholarly documents but has never been applied to mapping knowledge domains represented on Wikipedia.

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