Abstract
With the popularization of Internet social networking service, the results of association data mining between friend dynamic, microblog and moments that user posting and giving feedback information, which have important influence on government planning, business management and personal affairs decision-making activities. This paper studies the data mining technology of social network related information, analyzes the text data in social network by using the finite state automata (DFSA) and word frequency - reverse file frequency (TF-IDF), and using tree algorithm to sort the data. The simulation results show that this method can realize the classification data mining of social network related information.
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References
Shi, Y., Yuan, Y.: Research on the mode of information dissemination based on social network. Libr. Trib. (06) 220–223 (2009)
Lu, D., Li, S., Xu, C.: DFSA Algorithm for Adaptive Frame Length Adjustment with CHI Tagging. J. Harbin Univ. Sci. Technol. (01), 56–60 (2015)
Yang, S., Wang, J., Dai, B., Li, X., Jiang, Y., Liu, Y.: Research status and prospect of user behavior in online social networks. Bull. Chin. Acad. Sci. (02), 200–215 (2015)
Yao, Q., Ma, H., Yan, H., Chen, Q.: Analysis of individual behavior of social network users from the perspective of psychology. Adv. Psychol. Sci. 22(10), 1647–1659 (2014)
Huang, F., Peng, J., Ning, L.: An evolutionary model of social network views based on information entropy. Acta Phys. Sin. (16), 16–24 (2014)
Li, H., Zhou, Z.: Early warning system of university students’ grade based on data mining. J. Daqing Pet. Inst. (04), 91–95 (2011)
Wu, K.: Machine learning based prediction system for student grading and research. J. Taiyuan Urban Vocat. Techn. Coll. (12), 178–180 (2016)
Wang, Y., Wang, P.: Study on construction of early warning system for college students. Shanghai Educ. Eval. Res. (03), 36–40 (2014)
Lu, D., Ling X.: DFSA algorithm for unequal long time slots in full subgroup. Technol. Meas. Control (09), 55–59 (2013)
Sun, J., Wang, X.: Adaptive fuzzy decision tree algorithm. Comput. Eng. Des. 34(02), 649–653 (2013)
Li, Q., Zhou, X., Wang, L., Zhou, W.: Minimum combination method for mining maximal frequent sets. Appl. Res. Comput. 3(03), 702–704 (2008)
Gao, C., Shen, D., Yu, G., Nie, T., Kou, Y.: A method for mining frequent sets based on uncertain data. Proc. Conf. Natl. Database Churches 82–87 (2008)
Chen, X.: A frequent mining of association rules with constraints. Comput. Eng. Appl. (02), 205–208 (2003)
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Jiang, Y., Mei, X., Sun, G. (2018). Research on Data Mining Technology of Social Network Associated Information. In: Liu, S., Glowatz, M., Zappatore, M., Gao, H., Jia, B., Bucciero, A. (eds) e-Learning, e-Education, and Online Training. eLEOT 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 243. Springer, Cham. https://doi.org/10.1007/978-3-319-93719-9_3
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DOI: https://doi.org/10.1007/978-3-319-93719-9_3
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