Guided genetic algorithm for the influence maximization problem
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238700" target="_blank" >RIV/61989100:27240/17:10238700 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-62389-4_52" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-62389-4_52</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-62389-4_52" target="_blank" >10.1007/978-3-319-62389-4_52</a>
Alternative languages
Result language
angličtina
Original language name
Guided genetic algorithm for the influence maximization problem
Original language description
Influence maximization is a hard combinatorial optimization problem. It requires the identification of an optimum set of k network vertices that triggers the activation of a maximum total number of remaining network nodes with respect to a chosen propagation model. The problem is appealing because it is provably hard and has a number of practical applications in domains such as data mining and social network analysis. Although there are many exact and heuristic algorithms for influence maximization, it has been tackled by metaheuristic and evolutionary methods as well. This paper presents and evaluates a new evolutionary method for influence maximization that employs a recent genetic algorithm for fixed–length subset selection. The algorithm is extended by the concept of guiding that prevents selection of infeasible vertices, reduces the search space, and effectively improves the evolutionary procedure. © 2017, Springer International Publishing AG.
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
<a href="/en/project/GA15-06700S" target="_blank" >GA15-06700S: Unconventional Control of Complex Systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 10392
ISBN
978-3-319-62388-7
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
12
Pages from-to
630-641
Publisher name
Springer
Place of publication
Cham
Event location
Hongkong
Event date
Aug 3, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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