BibTex RIS Kaynak Göster

Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği

Yıl 2018, Cilt: 8 Sayı: 1, 30 - 37, 01.01.2018

Öz

Oluşan ve kaybolan birliktelik örüntüleri, frekansları destekleri zamanla artan ve azalan birliktelik örüntüleri olarak tanımlanır. Bu örüntülerin keşfedilmesi finans ve haberleşme servisleri, halk sağlığı, ve hidroklimatik çalışmalar gibi uygulama alanları için önemlidir. Klasik birliktelik örüntü madenciliği algoritmaları birliktelik örüntülerinin zamanla nasıl değiştiklerini göz önüne almazlar. Bir birliktelik örüntüsünün destek değeri zamanla değişiyor ise bu örüntü oluşan veya kaybolan örüntü olarak tanımlanabilir. Bu çalışmada, zamanla gelişen birliktelik örüntülerinin oluşan ve kaybolan biliktelik örüntüleri gibi veri kümelerinden keşfine odaklanılmıştır. Bu örüntüleri keşfetmek için, Oluşan ve Kaybolan Birliktelik Örüntü Madencisi EVAPMiner olarak isimlendirilen özgün bir algoritma önerilmiştir. Önerilen algoritma, Türkiye hidroklimatik verileri üzerinde uygulanmıştır. Analizler, önerilen algoritmanın hidroklimatik veri kümelerindeki oluşan ve kaybolan birliktelik örüntülerinin keşfinde başarılı olduğunu ortaya koymuştur

Kaynakça

  • Agrawal, R., Imielinski, T., Swami, A. 1993. Mining Association Rules between Sets of Items in Large Databases. In the Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp: 207 - 216.
  • Agrawal, R., Srikant, R. 1994. Fast Algorithms for Mining Association Rules. In the Proceedings of the 1994 International Conference on Very Large Databases, pp: 487-499.
  • Alves, R., Rodriguez-Baena, D.S., Aguilar-Ruiz, J.S. 2009. Gene Association Analysis: A Survey of Frequent Pattern Mining from Gene Expression Data, Brief. in Bioinfor., 11: 210-224.
  • Apte, C., Liu, B., Pednault, E.P.D., Smyth, P. 2002. Business Applications of Data Mining, Commun. of the ACM, 45 (8): 49-53.
  • Cayan, D. R., Riddle, L. G., Aguado, E. 1993. The Influence of Precipitation and Temperature on Seasonal Streamflow in California. Water Res. Rese., 29: 1127–1140.
  • Celik, M., Dadaser-Celik, F., Dokuz, A.S. 2014. Discovery of Hydrometeorological Patterns. Turk. J. Electric. Engin. Comput. Sci., 22: 840-857.
  • Changnon, S. A., Kunkel, K. E. 1995. Climate-related fluctuations in Midwestern Floods During 1921-1985. J. Water Res. Plan. Manag., 121: 326-334.
  • Creighton, C., Hanash, S. 2003. Mining Gene Expression Databases for Association Rules, Bioinfor., 19 (1): 79-86.
  • Dadaser-Celik F, Cengiz, E. 2014. Wind speed trends over Turkey from 1975 to 2006. Int. J. Climat., 34: 1913-1927.
  • Dadaser-Celik, F., Celik, M., Dokuz, A.S. 2012. Associations between Stream Flow and Climatic Variables at Kızılırmak River Basin in Turkey. Glob. Nest J., 14 (3): 354-361.
  • Dadaser-Celik, F., Cengiz, E. 2012. Correlations of Stream Flow and Climatic Variables in Turkey. In the BALWOIS, pp: 1-1.
  • Dhanya, C.T., Nagesh Kumar, D. 2009. Data Mining for Evolution of Association Rules for Droughts and Floods in India Using Climate Inputs. J. Geophy. Res.: Atmosph., 114 (D2): D02102.
  • Du, X., Jin, R., Ding, L., Lee, V.E., John H. Thornton, J. 2009. Migration Motif: A Spatial - Temporal Pattern Mining Approach for Financial Markets. In the Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp: 1135-1144.
  • Han, J., Kamber, M., Pei, J. 2011. Data Mining: Concepts and Techniques, 3rd Edition, Morgan Kaufmann Publishers Inc., San Fransisco, 744pp.
  • Hidber, C. 1999. Online Association Rule Mining. Proceedings of the 1999 SIGMOD Inernational Conference on Management of Data, pp:145-156.
  • Kahya, E., Karabork, M.C. 2001. The Analysis of El Nino and La Nina Signals in Streamflows of Turkey, Int. J. of Climato., 21 (10): 1231-1250.
  • Khan, A., Khan, K., Baharudin, B.B. 2009. Frequent Patterns Minning of Stock Data Using Hybrid Clustering Association Algorithm. In the Proceedings of the International Conference on Information Management and Engineering, ICIME '09., pp: 667-671.
  • Kumar, D.N., Ish, M., Dhanya, C.T. 2009. Data Mining and It's Applications for Modelling Rainfall Extremes, J. of Hydra. Eng., 15 (SP.1): 25-51.
  • Li, L., Zhang, M. 2011. The Strategy of Mining Association Rule Based on Cloud Computing. In the Proceedings of the 2011 International Conference on Business Computing and Global Informatization, pp: 475-478.
  • Liu, B., Hsu, W., Ma, Y. 1999. Mining Association Rules with Multiple Minimum Supports. In the Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp: 337-341.
  • Mishra, S., Dwivedi, V.K., Saravanan, C., Pathak, K.K. 2013. Pattern Discovery in Hydrological Time Series Data Mining During the Monsoon Period of the High Flood Years in Brahmaputra River Basin. Int. J. Comput. Appl., 67 (6): 7-14.
  • Nahar, J., Imam, T., Tickle, K.S., Chen, Y.-P.P. 2013. Association Rule Mining to Detect Factors Which Contribute to Heart Disease in Males and Females, Exp. Syst. with Appl., 40 (4): 1086-1093.
  • Ngai, E.W.T., Xiu, L., Chau, D.C.K. 2009. Application of Data Mining Techniques in Customer Relationship Management: A Literature Review and Classification. Exp. Syst. with Appl., 36 (2, Part 2): 2592-2602.

Emerging and Vanishing Association Pattern Mining in Hydroclimatic Datasets

Yıl 2018, Cilt: 8 Sayı: 1, 30 - 37, 01.01.2018

Öz

Emerging and vanishing association patterns can be defined as association patterns whose frequencies supports get stronger and weaker over time, respectively. Discovering these patterns is important for several application domains such as financial and communication services, public health, and hydroclimatic studies. Classical association pattern mining algorithms do not consider how the strengths of association patterns change over time. An association pattern can be defined as an emerging or vanishing pattern when its support measure changes over time. In this paper, we focus on discovery of time evolving association patterns i.e., emerging and vanishing association patterns from datasets. To discover such patterns, a novel algorithm, named as Emerging and Vanishing Association Pattern Miner EVAPMiner algorithm, was proposed. The proposed algorithm was evaluated using hydroclimatic dataset of Turkey. The analyses showed that the proposed algorithm successfully detects emerging and vanishing association patterns in hydroclimatic datasets.

Kaynakça

  • Agrawal, R., Imielinski, T., Swami, A. 1993. Mining Association Rules between Sets of Items in Large Databases. In the Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp: 207 - 216.
  • Agrawal, R., Srikant, R. 1994. Fast Algorithms for Mining Association Rules. In the Proceedings of the 1994 International Conference on Very Large Databases, pp: 487-499.
  • Alves, R., Rodriguez-Baena, D.S., Aguilar-Ruiz, J.S. 2009. Gene Association Analysis: A Survey of Frequent Pattern Mining from Gene Expression Data, Brief. in Bioinfor., 11: 210-224.
  • Apte, C., Liu, B., Pednault, E.P.D., Smyth, P. 2002. Business Applications of Data Mining, Commun. of the ACM, 45 (8): 49-53.
  • Cayan, D. R., Riddle, L. G., Aguado, E. 1993. The Influence of Precipitation and Temperature on Seasonal Streamflow in California. Water Res. Rese., 29: 1127–1140.
  • Celik, M., Dadaser-Celik, F., Dokuz, A.S. 2014. Discovery of Hydrometeorological Patterns. Turk. J. Electric. Engin. Comput. Sci., 22: 840-857.
  • Changnon, S. A., Kunkel, K. E. 1995. Climate-related fluctuations in Midwestern Floods During 1921-1985. J. Water Res. Plan. Manag., 121: 326-334.
  • Creighton, C., Hanash, S. 2003. Mining Gene Expression Databases for Association Rules, Bioinfor., 19 (1): 79-86.
  • Dadaser-Celik F, Cengiz, E. 2014. Wind speed trends over Turkey from 1975 to 2006. Int. J. Climat., 34: 1913-1927.
  • Dadaser-Celik, F., Celik, M., Dokuz, A.S. 2012. Associations between Stream Flow and Climatic Variables at Kızılırmak River Basin in Turkey. Glob. Nest J., 14 (3): 354-361.
  • Dadaser-Celik, F., Cengiz, E. 2012. Correlations of Stream Flow and Climatic Variables in Turkey. In the BALWOIS, pp: 1-1.
  • Dhanya, C.T., Nagesh Kumar, D. 2009. Data Mining for Evolution of Association Rules for Droughts and Floods in India Using Climate Inputs. J. Geophy. Res.: Atmosph., 114 (D2): D02102.
  • Du, X., Jin, R., Ding, L., Lee, V.E., John H. Thornton, J. 2009. Migration Motif: A Spatial - Temporal Pattern Mining Approach for Financial Markets. In the Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp: 1135-1144.
  • Han, J., Kamber, M., Pei, J. 2011. Data Mining: Concepts and Techniques, 3rd Edition, Morgan Kaufmann Publishers Inc., San Fransisco, 744pp.
  • Hidber, C. 1999. Online Association Rule Mining. Proceedings of the 1999 SIGMOD Inernational Conference on Management of Data, pp:145-156.
  • Kahya, E., Karabork, M.C. 2001. The Analysis of El Nino and La Nina Signals in Streamflows of Turkey, Int. J. of Climato., 21 (10): 1231-1250.
  • Khan, A., Khan, K., Baharudin, B.B. 2009. Frequent Patterns Minning of Stock Data Using Hybrid Clustering Association Algorithm. In the Proceedings of the International Conference on Information Management and Engineering, ICIME '09., pp: 667-671.
  • Kumar, D.N., Ish, M., Dhanya, C.T. 2009. Data Mining and It's Applications for Modelling Rainfall Extremes, J. of Hydra. Eng., 15 (SP.1): 25-51.
  • Li, L., Zhang, M. 2011. The Strategy of Mining Association Rule Based on Cloud Computing. In the Proceedings of the 2011 International Conference on Business Computing and Global Informatization, pp: 475-478.
  • Liu, B., Hsu, W., Ma, Y. 1999. Mining Association Rules with Multiple Minimum Supports. In the Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp: 337-341.
  • Mishra, S., Dwivedi, V.K., Saravanan, C., Pathak, K.K. 2013. Pattern Discovery in Hydrological Time Series Data Mining During the Monsoon Period of the High Flood Years in Brahmaputra River Basin. Int. J. Comput. Appl., 67 (6): 7-14.
  • Nahar, J., Imam, T., Tickle, K.S., Chen, Y.-P.P. 2013. Association Rule Mining to Detect Factors Which Contribute to Heart Disease in Males and Females, Exp. Syst. with Appl., 40 (4): 1086-1093.
  • Ngai, E.W.T., Xiu, L., Chau, D.C.K. 2009. Application of Data Mining Techniques in Customer Relationship Management: A Literature Review and Classification. Exp. Syst. with Appl., 36 (2, Part 2): 2592-2602.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Research Article
Yazarlar

Mete Çelik Bu kişi benim

Ahmet Şakir Dokuz Bu kişi benim

Filiz Dadaşer-çelik Bu kişi benim

Yayımlanma Tarihi 1 Ocak 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 8 Sayı: 1

Kaynak Göster

APA Çelik, M., Dokuz, A. Ş., & Dadaşer-çelik, F. (2018). Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği. Karaelmas Fen Ve Mühendislik Dergisi, 8(1), 30-37.
AMA Çelik M, Dokuz AŞ, Dadaşer-çelik F. Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği. Karaelmas Fen ve Mühendislik Dergisi. Ocak 2018;8(1):30-37.
Chicago Çelik, Mete, Ahmet Şakir Dokuz, ve Filiz Dadaşer-çelik. “Hidroklimatik Veritabanlarında Oluşan Ve Kaybolan Birliktelik Örüntülerinin Madenciliği”. Karaelmas Fen Ve Mühendislik Dergisi 8, sy. 1 (Ocak 2018): 30-37.
EndNote Çelik M, Dokuz AŞ, Dadaşer-çelik F (01 Ocak 2018) Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği. Karaelmas Fen ve Mühendislik Dergisi 8 1 30–37.
IEEE M. Çelik, A. Ş. Dokuz, ve F. Dadaşer-çelik, “Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği”, Karaelmas Fen ve Mühendislik Dergisi, c. 8, sy. 1, ss. 30–37, 2018.
ISNAD Çelik, Mete vd. “Hidroklimatik Veritabanlarında Oluşan Ve Kaybolan Birliktelik Örüntülerinin Madenciliği”. Karaelmas Fen ve Mühendislik Dergisi 8/1 (Ocak 2018), 30-37.
JAMA Çelik M, Dokuz AŞ, Dadaşer-çelik F. Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği. Karaelmas Fen ve Mühendislik Dergisi. 2018;8:30–37.
MLA Çelik, Mete vd. “Hidroklimatik Veritabanlarında Oluşan Ve Kaybolan Birliktelik Örüntülerinin Madenciliği”. Karaelmas Fen Ve Mühendislik Dergisi, c. 8, sy. 1, 2018, ss. 30-37.
Vancouver Çelik M, Dokuz AŞ, Dadaşer-çelik F. Hidroklimatik Veritabanlarında Oluşan ve Kaybolan Birliktelik Örüntülerinin Madenciliği. Karaelmas Fen ve Mühendislik Dergisi. 2018;8(1):30-7.