When social computing meets soft computing: opportunities and insights View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Fei Hao, Doo-Soon Park, Zheng Pei

ABSTRACT

The characteristics of the massive social media data, diverse mobile sensing devices as well as the highly complex and dynamic user’s social behavioral patterns have led to the generation of huge amounts of high dimension, uncertain, imprecision and noisy data from social networks. Thanks to the emerging soft computing techniques which unlike the conventional hard computing. It is widely used for coping with the tolerant of imprecision, uncertainty, partial truth, and approximation. One of the most important and promising applications is social network analysis (SNA) that is the process of investigating social structures and relevant properties through the use of network and graph theories. This paper aims to survey various SNA approaches using soft computing techniques such as fuzzy logic, formal concept analysis, rough sets theory and soft set theory. In addition, the relevant software packages about SNA are clearly summarized. More... »

PAGES

8

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13673-018-0131-z

    DOI

    http://dx.doi.org/10.1186/s13673-018-0131-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1101762650


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