F-Mapper: A Fuzzy Mapper clustering algorithm

Bui, Quang-Thinh; Vo, Bay; Nguyen, Hoang-Anh T.; Hùng, Nguyễn Quốc; Snåšel, Václav

doi:10.1016/j.knosys.2019.105107

Cited by 26 publications

(16 citation statements)

References 35 publications

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“…Future works related to the plithogenic entropy include studying more examples of entropy measures for plithogenic sets with structures different from the one mentioned in Theorem 1, and to apply the different types of entropy measure for plithogenic sets onto real life datasets. We are also working on developing entropy measures for other types of plithogenic sets such as plithogenic intuitionistic fuzzy sets and plithogenic neutrosophic sets, and the study of the application of these measures in solving real world problems using real life datasets [36][37][38][39][40][41][42][43].…”

Section: Discussionmentioning

confidence: 99%

Entropy Measures for Plithogenic Sets and Applications in Multi-Attribute Decision Making

et al. 2020

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Plithogenic set is an extension of the crisp set, fuzzy set, intuitionistic fuzzy set, and neutrosophic sets, whose elements are characterized by one or more attributes, and each attribute can assume many values. Each attribute has a corresponding degree of appurtenance of the element to the set with respect to the given criteria. In order to obtain a better accuracy and for a more exact exclusion (partial order), a contradiction or dissimilarity degree is defined between each attribute value and the dominant attribute value. In this paper, entropy measures for plithogenic sets have been introduced. The requirements for any function to be an entropy measure of plithogenic sets are outlined in the axiomatic definition of the plithogenic entropy using the axiomatic requirements of neutrosophic entropy. Several new formulae for the entropy measure of plithogenic sets are also introduced. The newly introduced entropy measures are then applied to a multi-attribute decision making problem related to the selection of locations.

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Section: Discussionmentioning

confidence: 99%

Entropy Measures for Plithogenic Sets and Applications in Multi-Attribute Decision Making

et al. 2020

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“…The latter is still an important problem, as there is still no clear methodology for parameter selection. In [6, 44] the authors explore ways to attack this problem using category theory.…”

Section: Methodologiesmentioning

confidence: 99%

Quantifying antibody dynamics of severe and non-severe patients with COVID-19

Ordonez-Jimenez¹,

Blanco-Rodríguez²,

Almocera

et al. 2022

Preprint

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COVID-19 pandemic is a major public health threat with unanswered questions regarding the role of the immune system in the severity level of the disease. In this paper, based on antibody kinetic data of patients with different disease severity, topological data analysis highlights clear differences in the shape of antibody dynamics between three groups of patients, which were non-severe, severe, and one intermediate case of severity. Subsequently, different mathematical models were developed to quantify the dynamics between the different severity groups. The best model was the one with the lowest media value of Akaike Information Criterion for all groups of patients. Although it has been reported high IgG level in severe patients, our findings suggest that IgG antibodies in severe patients may be less effective than non-severe patients due to early B cell production and early activation of the seroconversion process from IgM to IgG antibody.

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“…The low-dimensional representation is not accurate; however, it saves the topological shape of the data and is less sensitive to the selected distance metric. The Mapper algorithm has been applied to various problems such as 3D object recognition [ 59 ], bioinformatics [ 60 ], data visualization [ 61 ], and cancer detection [ 62 ]. The Mapper algorithm is applied to the 150-dimensions vectors to group them.…”

Section: Methodsmentioning

confidence: 99%

Track Iran's national COVID-19 response committee’s major concerns using two-stage unsupervised topic modeling

Kaveh-Yazdy

Zarifzadeh

2021

International Journal of Medical Informatics

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Background Since the World Health Organization (WHO) declared the COVID-19 as a Public Health Emergency of International Concern (PHEIC) on January 31, 2020, governments have been enfaced with crisis for timely responses. The efficacy of these responses directly depends on the social behaviors of the target society. People react to these actions with respect to the information they received from different channels, such as news and social networks. Thus, analyzing news demonstrates a brief view of the information users received during the outbreak. Methods The raw data used in this study is collected from official news channels of news wires and agencies in Telegram messenger, which exceeds 2,400,000 posts. The posts that are quoted by NCRC’s members are collected, cleaned, and divided into sentences. The topic modeling and tracking are utilized in a two-stage framework, which is customized for this problem to separate miscellaneous sentences from those presenting concerns. The first stage is fed with embedding vectors of sentences where they are grouped by the Mapper algorithm. Sentences belonging to singleton nodes are labeled as miscellaneous sentences. The remained sentences are vectorized, adopting Tf-IDF weighting schema in the second stage and topically modeled by the LDA method. Finally, relevant topics are aligned to the list of policies and actions, named topic themes, that are set up by the NCRC. Results Our results show that major concerns presented in about half of the sentences are (1) PCR lab. test, diagnosis, and screening, (2) Closure of the education system, and (3) awareness actions about washing hands and facial mask usage. Among the eight themes, intra-provincial travel and traffic restrictions, as well as briefing the national and provincial status, are under-presented. The timeline of concerns annotated by the preventive actions illustrates the changes in concerns addressed by NCRC. This timeline shows that although the announcements and public responses are not lagged behind the events, but cannot be considered as timely. Furthermore, the fluctuating series of concerns reveal that the NCRC has not a long-time response map, and members react to the closest announced policy/act. Conclusion The results of our study can be used as a quantitative indicator for evaluating the availability of an on-time public response of Iran’s NCRC during the first three months of the outbreak. Moreover, it can be used in comparative studies to investigate the differences between awareness acts in various countries. Results of our customized-design framework showed that about one-third of the discussions of the NCRC’s members cover miscellaneous topics that must be removed from the data.

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F-Mapper: A Fuzzy Mapper clustering algorithm

Cited by 26 publications

References 35 publications

Entropy Measures for Plithogenic Sets and Applications in Multi-Attribute Decision Making

Entropy Measures for Plithogenic Sets and Applications in Multi-Attribute Decision Making

Quantifying antibody dynamics of severe and non-severe patients with COVID-19

Track Iran's national COVID-19 response committee’s major concerns using two-stage unsupervised topic modeling

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