Community detection in online social network using graph embedding and hierarchical clustering
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10244588" target="_blank" >RIV/61989100:27240/19:10244588 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-01818-4_26" target="_blank" >http://dx.doi.org/10.1007/978-3-030-01818-4_26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-01818-4_26" target="_blank" >10.1007/978-3-030-01818-4_26</a>
Alternative languages
Result language
angličtina
Original language name
Community detection in online social network using graph embedding and hierarchical clustering
Original language description
The community detection plays an important role in social network analysis. It can be used to find users that behave in a similar manner, detect groups of interests, cluster users in e-commerce application such as their taste or shopping habits, etc. In this paper, we proposed an algorithm to detect the community in online social networks. Our algorithm represents the nodes and the relationships in the social networks using a vector, agglomerative clustering (the most famous clustering algorithm) will cluster those vectors to figure out the communities. The experimental results show that our algorithm performs better traditional agglomerative clustering because of the ability to detect the community which has better modularity value. (C) Springer Nature Switzerland AG 2019.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 874
ISBN
978-3-030-01817-7
ISSN
2194-5357
e-ISSN
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Number of pages
10
Pages from-to
263-272
Publisher name
Springer
Place of publication
Basilej
Event location
Soči
Event date
Sep 17, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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