Data Mining Meets HCI: Data and Visual Analytics of Frequent Patterns

详细信息    查看全文

• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9853
• 期：1
• 页码：289-293
• 全文大小：1,848 KB
• 参考文献：1.Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: VLDB 1994, pp. 487–499 (1994)
  2.Andrienko, N.V., Andrienko, G.L., Fuchs, G., Jankowski, P.: Visual analytics methodology for scalable and privacy-respectful discovery of place semantics from episodic mobility data. In: Bifet, A., May, M., Zadrozny, B., Gavalda, R., Pedreschi, D., Bonchi, F., Cardoso, J., Spiliopoulou, M. (eds.) ECML PKDD 2015 Part III. LNCS, vol. 9286, pp. 254–258. Springer, Heidelberg (2015)CrossRef
  3.Börner, M., Rhode, W., Ruhe, T., Morik, K.: Discovering neutrinos through data analytics. In: Bifet, A., May, M., Zadrozny, B., Gavalda, R., Pedreschi, D., Bonchi, F., Cardoso, J., Spiliopoulou, M. (eds.) ECML PKDD 2015. LNCS, vol. 9286, pp. 208–212. Springer, Heidelberg (2015)CrossRef
  4.Carmichael, C.L., Hayduk, Y., Leung, C.K.: Visually contrast two collections of frequent patterns. In: IEEE ICDM Workshops 2011, pp. 1128–1135 (2011)
  5.Carmichael, C.L., Leung, C.K.: CloseViz: visualizing useful patterns. In: ACM SIGKDD Workshop on UP 2010, pp. 17–26 (2010)
  6.Keim, D.A., Kriegel, H.-P.: Visualization techniques for mining large databases: a comparison. IEEE TKDE 8(6), 923–938 (1996)
  7.Leung, C.K., Carmichael, C.L.: FpVAT: a visual analytic tool for supporting frequent pattern mining. ACM SIGKDD Explor. 11(2), 39–48 (2009)CrossRef
  8.Leung, C.K., Irani, P.P., Carmichael, C.L.: FIsViz: a frequent itemset visualizer. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 644–652. Springer, Heidelberg (2008)CrossRef
  9.Leung, C.K., Irani, P.P., Carmichael, C.L.: WiFIsViz: effective visualization of frequent itemsets. In: IEEE ICDM, pp. 875–880 (2008)
  10.Leung, C.K., Jiang, F.: RadialViz: an orientation-free frequent pattern visualizer. In: Tan, P.-N., Chawla, S., Ho, C.K., Bailey, J. (eds.) PAKDD 2012, Part II. LNCS, vol. 7302, pp. 322–334. Springer, Heidelberg (2012)CrossRef
  11.Leung, C.K., Jiang, F., Irani, P.P.: FpMapViz: a space-filling visualization for frequent patterns. In: IEEE ICDM Workshops, pp. 804–811 (2011)
  12.Leung, C.K., Kononov, V.V., Pazdor, A.G.M.: PyramidViz: visual analytics and big data visualization of frequent patterns. In: IEEE DASC/DataCom 2016 (2016)
  
• 作者单位：Carson K. Leung (20)
  Christopher L. Carmichael (20)
  Yaroslav Hayduk (20) (21)
  Fan Jiang (20)
  Vadim V. Kononov (20)
  Adam G. M. Pazdor (20)
  
  20. University of Manitoba, Winnipeg, MB, Canada
  21. Université de Neuchâtel, Neuchâtel, Switzerland
  
• 丛书名：Machine Learning and Knowledge Discovery in Databases
• ISBN：978-3-319-46131-1
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9853

文摘

As a popular data mining tasks, frequent pattern mining discovers implicit, previously unknown and potentially useful knowledge in the form of sets of frequently co-occurring items or events. Many existing data mining algorithms return to users with long textual lists of frequent patterns, which may not be easily comprehensible. As a picture is worth a thousand words, having a visual means for humans to interact with computers would be beneficial. This is when human-computer interaction (HCI) research meets data mining research. In particular, the popular HCI task of data and result visualization could help data miners to visualize the original data and to analyze the mined results (in the form of frequent patterns). In this paper, we present a few systems for data and visual analytics of frequent patterns, which integrate (i) data analytics and mining with (ii) data and result visualization.