Matches in SemOpenAlex for { <https://semopenalex.org/work/W3118257130> ?p ?o ?g. }
- W3118257130 endingPage "10040" @default.
- W3118257130 startingPage "10025" @default.
- W3118257130 abstract "In the past few decades, although people have conducted in-depth research on community detection in one-mode networks, community detection in bipartite networks has not been extensively researched. In this paper, we propose an improved artificial bee colony algorithm named IABC-BN, which is used to detect the communities in two-mode graphs (i.e. bipartite graphs) with two kinds of vertices in the cluster (i.e. community). Firstly, this paper proposed a novel population initialization process of artificial bee colony (ABC) method for two-mode graph cluster identification. This initialization method can improve the diversity of initial population of ABC and speed up its convergence rate. Secondly, in the employed bee search step of the algorithm, a new combinatorial search equation is proposed. This equation is guided by the global optimal solution and the better neighbour solution of the current solution. By using this combination equation and the increased parameter perturbation frequency, the exploitation ability of the algorithm is further enhanced. Thirdly, in the onlooker bees step, another new combination search equation is also proposed. This equation improves the exploitation level of the algorithm, and an opposition based studying method is employed to promote the exploitation ability of the algorithm. Lastly, in scout bee stage, a probability threshold $beta $ is introduced to enhance the exploration ability of the algorithm and improve the population diversity of the algorithm. To our knowledge, the IABC-BN method presented in this paper is the first ABC method used to cluster identification in two-mode graphs with two kinds of vertices in the cluster. For verifying the accuracy of the results of the proposed method, a large number of experiments are carried out making use of synthetic bipartite graphs and real bipartite graphs. The test outcomes show that this algorithm is an excellent algorithm for cluster discovery in two-mode graph." @default.
- W3118257130 created "2021-01-18" @default.
- W3118257130 creator A5046597133 @default.
- W3118257130 creator A5056368740 @default.
- W3118257130 creator A5067423683 @default.
- W3118257130 date "2021-01-01" @default.
- W3118257130 modified "2023-10-17" @default.
- W3118257130 title "An Improved Artificial Bee Colony Algorithm for Community Detection in Bipartite Networks" @default.
- W3118257130 cites W131619556 @default.
- W3118257130 cites W1584510240 @default.
- W3118257130 cites W1965811262 @default.
- W3118257130 cites W1977042441 @default.
- W3118257130 cites W1982970548 @default.
- W3118257130 cites W1983601936 @default.
- W3118257130 cites W1987643017 @default.
- W3118257130 cites W2011890778 @default.
- W3118257130 cites W2013849176 @default.
- W3118257130 cites W2014442726 @default.
- W3118257130 cites W2014747921 @default.
- W3118257130 cites W2023546247 @default.
- W3118257130 cites W2032273054 @default.
- W3118257130 cites W2037063559 @default.
- W3118257130 cites W2038609634 @default.
- W3118257130 cites W2045239993 @default.
- W3118257130 cites W2046224350 @default.
- W3118257130 cites W2047626401 @default.
- W3118257130 cites W2049450500 @default.
- W3118257130 cites W2063909949 @default.
- W3118257130 cites W2064319317 @default.
- W3118257130 cites W2066780923 @default.
- W3118257130 cites W2067539801 @default.
- W3118257130 cites W2076272170 @default.
- W3118257130 cites W2082555634 @default.
- W3118257130 cites W2086757495 @default.
- W3118257130 cites W2093284687 @default.
- W3118257130 cites W2093786661 @default.
- W3118257130 cites W2103582124 @default.
- W3118257130 cites W2112766038 @default.
- W3118257130 cites W2128366083 @default.
- W3118257130 cites W2133133974 @default.
- W3118257130 cites W2144317842 @default.
- W3118257130 cites W2151936673 @default.
- W3118257130 cites W2160249427 @default.
- W3118257130 cites W2162745921 @default.
- W3118257130 cites W2169064301 @default.
- W3118257130 cites W2473633166 @default.
- W3118257130 cites W2567368484 @default.
- W3118257130 cites W2588687305 @default.
- W3118257130 cites W2611903466 @default.
- W3118257130 cites W2740985535 @default.
- W3118257130 cites W2765496437 @default.
- W3118257130 cites W2768306412 @default.
- W3118257130 cites W2769535977 @default.
- W3118257130 cites W2772410907 @default.
- W3118257130 cites W2773450466 @default.
- W3118257130 cites W2780693286 @default.
- W3118257130 cites W2789168111 @default.
- W3118257130 cites W2807875003 @default.
- W3118257130 cites W2888224868 @default.
- W3118257130 cites W2890111090 @default.
- W3118257130 cites W2901326905 @default.
- W3118257130 cites W2914801031 @default.
- W3118257130 cites W2919191060 @default.
- W3118257130 cites W2922470279 @default.
- W3118257130 cites W2926086152 @default.
- W3118257130 cites W2933806414 @default.
- W3118257130 cites W2949598766 @default.
- W3118257130 cites W2952929724 @default.
- W3118257130 cites W2954335066 @default.
- W3118257130 cites W2959207112 @default.
- W3118257130 cites W2967606169 @default.
- W3118257130 cites W3041618506 @default.
- W3118257130 cites W3094479573 @default.
- W3118257130 cites W919304072 @default.
- W3118257130 doi "https://doi.org/10.1109/access.2021.3050752" @default.
- W3118257130 hasPublicationYear "2021" @default.
- W3118257130 type Work @default.
- W3118257130 sameAs 3118257130 @default.
- W3118257130 citedByCount "3" @default.
- W3118257130 countsByYear W31182571302021 @default.
- W3118257130 countsByYear W31182571302022 @default.
- W3118257130 countsByYear W31182571302023 @default.
- W3118257130 crossrefType "journal-article" @default.
- W3118257130 hasAuthorship W3118257130A5046597133 @default.
- W3118257130 hasAuthorship W3118257130A5056368740 @default.
- W3118257130 hasAuthorship W3118257130A5067423683 @default.
- W3118257130 hasBestOaLocation W31182571301 @default.
- W3118257130 hasConcept C11413529 @default.
- W3118257130 hasConcept C114466953 @default.
- W3118257130 hasConcept C126255220 @default.
- W3118257130 hasConcept C132525143 @default.
- W3118257130 hasConcept C144024400 @default.
- W3118257130 hasConcept C149923435 @default.
- W3118257130 hasConcept C154945302 @default.
- W3118257130 hasConcept C162324750 @default.
- W3118257130 hasConcept C197657726 @default.
- W3118257130 hasConcept C199360897 @default.
- W3118257130 hasConcept C2777303404 @default.