2026-09-19T07:06:13Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/29451 2023-07-10 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Han, Jiawei Han, Jiawei Zhai, ChengXiang Chang, Kevin C-C. Schatz, Bruce R. Kim, Sangkyum 2012-02-01T00:46:55Z 2014-02-01T11:00:27Z 2012-02-01T00:46:55Z 2011-12 Pattern mining has been a hot issue since it was first proposed for market basket analysis. Even though pattern mining is one of the oldest topic in data mining domain, there are still many ongoing challenges to overcome on this subject since the scale of the data size is getting bigger and the complexity of data structure is getting more complicated. This dissertation discusses several pattern mining tasks, challenges associated with them, and algorithm designs that overcome these challenges. Specifically, we design and implement techniques for (1) directly mining discriminative patterns from a numeric valued feature set of k-embedded edge subtrees given labeled training data, (2) mining top correlated patterns from transactional databases with low minimum support, and (3) mining flipping correlation patterns from transactional databases given item hierarchy. We evaluate our solutions by conducting comprehensive experiments on large-scale synthetic and real world datasets. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2011-09-23T18:08:57Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Kim_Sangkyum.pdf: 1823074 bytes, checksum: 3c8fd019952139afc8b2d501a4e9a0b2 (MD5) Made available in DSpace on 2012-02-01T00:46:55Z (GMT). No. of bitstreams: 2 Kim_Sangkyum.pdf: 1823074 bytes, checksum: 3c8fd019952139afc8b2d501a4e9a0b2 (MD5) license.txt: 4059 bytes, checksum: d6544e66b106387a13daa193851b34e5 (MD5) Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by William Ingram (wingram2@illinois.edu) on 2012-02-01T00:50:25Z Item is restricted until 2014-02-01T00:50:07Z Item reinstated by Sarah Shreeves (sshreeve@illinois.edu) on 2014-02-01T11:00:27Z Item was in collections: Graduate Theses and Dissertations at Illinois (ID: 204) Dissertations and Theses - Computer Science (ID: 587) No. of bitstreams: 3 Kim_Sangkyum.pdf.txt: 211029 bytes, checksum: cca8dd4c4a1517192075d615c2913802 (MD5) Kim_Sangkyum.pdf: 1823074 bytes, checksum: 3c8fd019952139afc8b2d501a4e9a0b2 (MD5) license.txt: 4059 bytes, checksum: d6544e66b106387a13daa193851b34e5 (MD5) Item released from any restrictions by Sarah Shreeves (sshreeve@illinois.edu) on 2014-02-01T11:00:27Z http://hdl.handle.net/2142/29451 en Copyright 2011 Sangkyum Kim sophisticated pattern mining k-embedded-edge subtree discriminative pattern correlated pattern flipping correlation pattern Mining sophisticated patterns for classification and correlation analysis Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Dissertation Ph.D. PHD:Computer Science -UIUC 10KS0112PHD