Analyzing and Visualizing Relationship Networks
نویسندگان
چکیده
This project is designed to detect the hidden relationships between risks, model them and visualize them. The technique is based on a mixture of text clustering and text classification. Firstly, the raw risks are preprocessed and transformed into the desired format. Then Latent Dirichlet Allocation (LDA) is applied to the risks as a cluster technique to discover the hidden thematic topics that can be used to group risks. After obtaining the topic structure, new risks can be classified into these topics using techniques like Naïve Bayes (NB). The approach is able to not only model the relationships between existing risks, but also model the relationships between “new” risks and “old” risks. In addition, a JavaScript library called D3 has been utilized to visualize the relationship network.
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تاریخ انتشار 2013