| Author: | Wu, Chunxue |
| Title: | Graph mining applied on social media |
| Degree: | M.Sc. |
| Year: | 2011 |
| Subject: | Graphic methods. Data mining. Social media. Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Computing |
| Pages: | ix, 98 leaves : ill. ; 30 cm. |
| Language: | English |
| Abstract: | In the first of the paper, we give the detailed survey about all kinds of the algorithms for different direction for the structure-data such as the graph-based representation. We want to find the shortage of them and find the interesting one to further study. We propose to mine a set of rules from the social media data. The association rules, clustering algorithm of K- Means, the classification of ID3 and the fuzzy C mean algorithm. We try to analyze this question step by step and give the conclusion. In doing this part, we try to use different tools for one algorithm and get the results. Although we give the analysis and give the suggestion of which tools we may use, we do not apply the choice on the next part on the basic methods. In solving the basic parts, we notice that what the attributes are chosen is important. In this sense, we want to know the method to handle the attributes. Furthermore, we use a Java program to achieve this goal and give the result and analysis. In this problem, we also find that most of the attributes are overlap. Of course, it is a fuzzy problem. Then we use the more common way called FCM to solve this problem. In the process we try to use graph theory, there are some problems. At last, we give up this idea, but we would research this problem in the future about the more attributes and improve the fuzzy algorithm applied on this problem for social media data. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b2473584x.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.73 MB | Adobe PDF | View/Open |
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