By Dominik Slezak, Gerald Schaefer, Son T. Vuong, Yoo-Sung Kim
This publication constitutes the complaints of the tenth overseas convention on energetic Media know-how, AMT 2014, held in Warsaw, Poland, in August 2014, held as a part of the 2014 net Intelligence Congress, WIC 2014. The forty seven complete papers awarded have been conscientiously reviewed and chosen from a variety of submissions. the themes of those papers surround energetic computers; interactive structures and functions of AMT-based platforms; energetic media computing device studying and information mining suggestions; AMT for the semantic net; social networks and cognitive foundations.
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All other edges in Ga which are not in G are termed as secondary similarities. We use the term similarity from now on to point to either primary or secondary similarity. Graph Clustering Using Mutual K-Nearest Neighbors 37 Mutual K-Nearest Neighbors (MKNN). We define a node affinity measure called Mutual K-nearest neighbor relationship on the augmented graph Ga based upon the node similarity values. As opposed to the traditional neighborhood affinity measure KNN, MKNN defines a two way relationship between nodes.
B)(c)(d)(e) The process of propagation on each community of G5 . These results show that our method is fit for the heterogeneous network. Specially, although some methods outperform the our method in community 3 and community 4, our method perform best in the whole network. Figure 5 compares the propagation results in both synthetic and benchmark networks. The propagation efficiency of our method with two strategies (FU and FR) in these networks is better than others. As for G1 and G2 networks, as shown in Figs.
By studying this case, we illustrate that the FU strategy can obtain the most important k nodes from a network through getting intersection elements from existing methods. 2 MAF Based on the Attribute Ranking Besides directly obtaining the intersectional results from existing ranking methods, this section proposes the other compound mode, named as Multiple Attribute Fusion method based on the attribute ranking (FR). The new strategy combines ranking results obtained by existing methods based on PageRank algorithm.