• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid
The Transactions of the Korean Institute of Electrical Engineers

The Transactions of the Korean Institute of Electrical Engineers

ISO Journal TitleTrans. Korean. Inst. Elect. Eng.
SCImago Journal & Country Rank

Journal Search

  1. Home
  2. Archive
  3. 2019-11 (Vol.68 No.11)
  4. 10.5370/KIEE.2019.68.11.1417
XML PDF INFO REF

References

1 
R. Agrawal, R. Srikant, 1994, Fast algorithms for mining association rules in large databases, in Proc. of the 20th International Conference on Very Large Databases, pp. 487-499Google Search
2 
J. Su, W. Chang, V. Tseng, 2017, Integrated mining of social and collaborative information for music recommend- ation, Data Science Patterns Recognition, Vol. 1, No. 1, pp. 13-30Google Search
3 
U. Yun, D. Kim, 2017, Mining of High Average-utility Itemsets using novel list Structure and pruning Strategy, Future Generation Computer System, Vol. 68, pp. 346-360DOI
4 
H. Yao, H. J. Hamilton, L. Geng, 2006, A unified framework for utility-based measures for mining itemsets., in Proc. of ACM SIGKDD 2nd Workshop Utility-Based Data Mining, pp. 28-37Google Search
5 
S. Krishnamoorthy, 2015, Pruning strategies for mining high utility itemsets, Expert Systems with Applications, Vol. 42, No. 5, pp. 2371-2381DOI
6 
S. Krishnamoorthy, 2017, Hminer: Efficiently mining high utility itemsets, Expert Systems with Applications, Vol. 90, No. c, pp. 168-183DOI
7 
J. C. W. Lin, T. Li, P. Fournier-Viger, T. P. Hong, J. Zhan, M. Voznak, 2016, An efficient algorithm to mine high average-utility itemsets, Adv. Eng. Inform., Vol. 30, No. 2, pp. 233-243DOI
8 
Y. Liu, W. Liao, A. Choudhary, 2005, A two-phase algorithm for fast discovery of high utility itemsets, in Proc. of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Vol. 3518, pp. 689-695Google Search
9 
C. F. Ahmed, S. K. Tanbeer, B. S. Jeong, Y. K. Lee, 2009, Efficient tree structures for high utility pattern mining in incremental databases, IEEE Trans. on Knowledge and Data Engineering, Vol. 21, No. 12, pp. 1708-1721DOI
10 
Y. C. Li, J. S. Yeh, C. C. Chang, 2008, Isolated items discarding strategy for discovering high utility itemsets, Data Knowl. Eng., Vol. 64, No. 1, pp. 198-217DOI
11 
V. S. Tseng, B. E. Shie, C. W. Wu, P. S. Yu, 2013, Efficient algorithms for mining high utility itemsets from transactional databases, IEEE Trans. on Knowledge and Data Engineering, Vol. 25, No. 8, pp. 1772-1786DOI
12 
H. Yao, H. J. Hamilton, C. J. Butz, 2004, A foundational approach to mining itemset utilities from databases, in Proc. of the Fourth SIAM International Conference on Data Mining, pp. 482-486DOI
13 
U. Yun, H. Ryang, K. H. Ryu, 2014, High utility itemset mining with techniques for reducing overestimated utilities and pruning candidates, Expert System with Applications, Vol. 41, No. 8, pp. 386-3878DOI
14 
V. Goyal, S. Dawar, 2015, UP-Hist tree: An efficient data structure for mining high utility patterns from transaction databases, in Proc. of the 19th International Database Engineering and Applications Symposium, pp. 56-61DOI
15 
E. Mengelkamp, J. Garttner, C. Weinhardt, 2018, Decent- ralizing energy systems through local energy markets: the LAMP-project, Proc. of Multikonferenz Wirtschaftsin- formatik, pp. 924-930Google Search
16 
J. Liu, K. Wang, B. C. M. Fung, 2015, Mining High Utility Patterns in One Phase without Generating Candidates, IEEE Trans. on Knowledge and Data Engineering, Vol. 28, No. 5, pp. 1245-1257DOI
17 
M. Liu, J. Qu, 2012, Mining high utility itemsets without candidate generation, in Proc. of the 21st ACM International Conference on Information and Knowledge Management, pp. 55-64DOI
18 
P. Fournier-Viger, C. W. Wu, S. Zida, V. S. Tseng, 2014, FHM: Faster high-utility itemset mining using estimated utility co-occurrence pruning, Foundations of Intelligent Systems, pp. 83-92DOI
19 
W. Song, Y. Liu, J. Li, 2014, BAHUI: Fast and Memory Efficient Mining of High Utility Itemsets Based on Bitmap, International Journal of Data Warehousing and Mining, Vol. 10, No. 1, pp. 1-15DOI