| Summary: | 碩士 === 國立清華大學 === 通訊工程研究所 === 101 === Currently, the community detection in networks has gathered a lot of attention. How-
ever, if we are only interested in certain nodes, then we need local community detection.
Moreover, If the graph is directed one, just like citation networks, then there would be
lots of dierences. A new way of searching papers by using relative centrality on di-
rected graph as our local community detection method is provided. Modications of our
undirected version to directed version are also been made. Then we have two methods
of random walk, we are going to show that by using general type of random walk with
walking length under two steps is better than the rst type of random walk with walking
length in single step. After our experiment, we can nd a larger size of community and
we believe our ranking order has more sense compared to only considering citation size,
because we take triangle into consideration, which means that our prior adding nodes
not only have direct link to the community but also have some two steps of links to the
community. Finally, we list some problems for our future works.
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