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ดร.โกเมศ อัมพวัน

Dr. Komate Amphawan

  • ตำแหน่ง : อาจารย์
  • Email :  komate@gmail.com
  • ห้องทำงาน : IF-908C
  • โทรศัพท์ : 
  • ประวัติการศึกษา :
  • สาขาที่สนใจ : 

>> Data Mining
>> Association Rule Mining
>> Web Mining
>> Text Mining
>> Natural Language Processing

  • ผลงาน :

>> Klangwisan, K., & Amphawan, K. (2017). Mining weighted-frequent-regular Itemsets from transactional database. In Proceedings of 9th International Conference on Knowledge and Smart Technologies 2017 (pp. 66-71). Pattaya: Thailand.

>> Laoviboon, S., & Amphawan, K. (2017). Mining High-Utility Itemsets with Irregular Occurrence. In Proceedings of 9th International Conference on Knowledge and Smart Technologies 2017 (pp. 89-94). Pattaya: Thailand.

>> Eisariyodom, S., & Amphawan, K. (2017). Discovering interesting itemsets based on change in regularity of occurrence. In Proceedings of 9th International Conference on Knowledge and Smart Technologies 2017 (pp. 138-143). Pattaya: Thailand.

>> K. Amphawan, J.Soulas, P. Lenca, “Mining top-k Episodes from Sensor Streams”, Procedia Computer Science(The 7th International Conference on Advances in Information Technology), vol. 69, pp.76-85, 2015.

>> K. Amphawan, A. Surarerks, “Pushing Regularity Constraint on High Utility Itemsets Mining”, The 2015 International Conference on Advanced Informatics: Concepts, Theory And Application (ICAICIT2015) [Best paper award]

>> K. Amphawan , P. Lenca, “Mining top-k frequent-regular closed patterns”, Expert Systems with Applications, Elsevier, vol. 42(21), pp. 7882-7894, 2015.

>> K. Amphawan, P.Sittichaitaweekul, “Mining top-k frequent-regular patterns based on user-given length constraints”, The 19th International Annual Symposium on Computational Science and Engineering

>> S. Chompaisal, K. Amphawan, A. Surarerks, “Mining N-most Interesting Multi-level Frequent Itemsets without Support Threshold”, Proceedings of Recent Advances in Information and Communication Technology.

>> P. Sittichaitaweekul, K. Amphawan, “Enhancing quality of results on Top-k Frequent-Regular Pattern mining”, Proceedings of International Conference on Engineering Science and Innovative Technology.

>> K. Amphawan and P. Lenca, “Mining top-k frequent-regular patterns based on user-given trade-off between frequency and regularity”, Proceeding of the 6th International Conference on Advances in Information Technology: IAIT-2013, Bangkok, Thailand, Springer.

>> K. Amphawan, “SST: An efficient suffix-sharing trie structure for dictionary lookup”, Proceedings of 7th Asia international conference on mathematical modeling and computer simulation.

>> K. Amphawan and A. Surarerks, “An efficient method for constructing dictionary based on decompounding words technique”, The 17th International Annual Symposium on Computational Science and Engineering.

>> K. Amphawan, P. Lenca, and A. Surarerks, “Mining top-k regular-frequent itemsets using database partitioning and support estimation”, Expert Systems with Applications, Volume 39, Issue 2, February 1, Pages 1924-1936.

>> K. Amphawan K, P. Lenca , and A. Surarerks, “Efficient mining top-k regular-frequent itemset using compressed tidsets”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7104 LNAI , pp. 124-135.

>> K. Amphawan, A. Surarerks and P. Lenca, “Mining periodic-frequent itemset with approximate periodicity using interval transaction-ids list tree”. Proceeding of The 3rd International Conference on Knowledge Discovery and Data Mining: WKDD 2010, Phuket, Thailand, January 9-10.

>> K. Amphawan, P. Lenca and A. Surarerks, “Mining top-k periodic-frequent pattern from transactional databases without support threshold”. Proceeding of the 3rd International Conference on Advances in Information Technology: IAIT-09, Bangkok, Thailand, December 1-5, ser. CCIS, vol. 55. Springer, pp. 18-29.

>> K. Amphawan and A. Surarerks, “Mining association rule using an improvement of frequent item tree “. Proceeding of the 2nd Joint Conference of Science and Software Engineering: JCSSE2005, Burapha University, Chonburi, Thailand, November 17-18.

>> K. Amphawan and A. Surarerks, “An approach of frequent item tree for association generation”. Proceedings of Artificial Intelligence and Soft Computing (ASC), Benidorm, Spain.

>> K. Amphawan and A. Surarerks, “Mining Association Rules with Frequent Item Tree”. Proceedings of the 8th National Computer Science and Engineering Conference:NCSEC2004, Songkhla, Thailand, October 21-22.