{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T08:07:32Z","timestamp":1779091652119,"version":"3.51.4"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,7,5]],"date-time":"2017-07-05T00:00:00Z","timestamp":1499212800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Big Data"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1186\/s40537-017-0077-4","type":"journal-article","created":{"date-parts":[[2017,7,4]],"date-time":"2017-07-04T21:26:34Z","timestamp":1499203594000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":193,"title":["Analysis of agriculture data using data mining techniques: application of big data"],"prefix":"10.1186","volume":"4","author":[{"given":"Jharna","family":"Majumdar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sneha","family":"Naraseeyappa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shilpa","family":"Ankalaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,7,5]]},"reference":[{"key":"77_CR1","unstructured":"Veenadhari S, Misra B, Singh CD. Data mining techniques for predicting crop productivity\u2014A review article. In: IJCST. 2011; 2(1)."},{"key":"77_CR2","unstructured":"Gleaso CP. Large area yield estimation\/forecasting using plant process models.paper presentation at the winter meeting American society of agricultural engineers palmer house, Chicago, Illinois. 1982; 14\u201317"},{"key":"77_CR3","doi-asserted-by":"crossref","unstructured":"Majumdar J, Ankalaki S. Comparison of clustering algorithms using quality metrics with invariant features extracted from plant leaves. In: Paper presented at international conference on computational science and engineering. 2016.","DOI":"10.1166\/asl.2017.10253"},{"issue":"3","key":"77_CR4","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1145\/331499.331504","volume":"31","author":"A Jain","year":"1999","unstructured":"Jain A, Murty MN, Flynn PJ. Data clustering: a review. ACM Comput Surv. 1999;31(3):264\u2013323.","journal-title":"ACM Comput Surv"},{"key":"77_CR5","volume-title":"Algorithms for clustering data","author":"AK Jain","year":"1988","unstructured":"Jain AK, Dubes RC. Algorithms for clustering data. New Jersey: Prentice Hall; 1988."},{"key":"77_CR6","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/3-540-28349-8_2","volume-title":"Grouping multidimensional data","author":"P Berkhin","year":"2006","unstructured":"Berkhin P. A survey of clustering data mining technique. In: Kogan J, Nicholas C, Teboulle M, editors. Grouping multidimensional data. Berlin: Springer; 2006. p. 25\u201372."},{"key":"77_CR7","volume-title":"Data mining: concepts and techniques","author":"J Han","year":"2001","unstructured":"Han J, Kamber M. Data mining: concepts and techniques. Massachusetts: Morgan Kaufmann Publishers; 2001."},{"key":"77_CR8","unstructured":"Ester M, Kriegel HP, Sander J, Xu X. A density-based algorithm for discovering clusters in large spatial databases with noise. In: Paper presented at International conference on knowledge discovery and data mining. 1996"},{"key":"77_CR9","unstructured":"Ramesh D, Vishnu Vardhan B. Data mining techniques and applications to agricultural yield data. In: International journal of advanced research in computer and communication engineering. 2013; 2(9)."},{"key":"77_CR10","first-page":"8","volume":"2014","author":"M MotiurRahman","year":"2014","unstructured":"MotiurRahman M, Haq N, Rahman RM. Application of data mining tools for rice yield prediction on clustered regions of Bangladesh. IEEE. 2014;2014:8\u201313.","journal-title":"IEEE"},{"key":"77_CR11","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S0016-7061(00)00088-4","volume":"101","author":"K Verheyen","year":"2001","unstructured":"Verheyen K, Adrianens M, Hermy S Deckers. High resolution continuous soil classification using morphological soil profile descriptions. Geoderma. 2001;101:31\u201348.","journal-title":"Geoderma"},{"issue":"2","key":"77_CR12","doi-asserted-by":"crossref","first-page":"313","DOI":"10.5424\/sjar\/2014122-4439","volume":"12","author":"Alberto Gonzalez-Sanchez","year":"2014","unstructured":"Gonzalez-Sanchez Alberto, Frausto-Solis Juan, Ojeda-Bustamante W. Predictive ability of machine learning methods for massive crop yield prediction. Span J Agric Res. 2014;12(2):313\u201328.","journal-title":"Span J Agric Res"},{"key":"77_CR13","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.compag.2015.11.018","volume":"121","author":"XE Pantazi","year":"2016","unstructured":"Pantazi XE, Moshou D, Alexandridis T, Mouazen AM. Wheat yield prediction using machine learning and advanced sensing techniques. Comput Electron Agric. 2016;121:57\u201365.","journal-title":"Comput Electron Agric"},{"key":"77_CR14","doi-asserted-by":"crossref","unstructured":"Veenadhari S, Misra B, Singh D. Machine learning approach for forecasting crop yield based on climatic parameters. In: Paper presented at international conference on computer communication and informatics (ICCCI-2014), Coimbatore. 2014.","DOI":"10.1109\/ICCCI.2014.6921718"},{"key":"77_CR15","first-page":"012012","volume":"31","author":"N Rahmah","year":"2016","unstructured":"Rahmah N, Sitanggang IS. Determination of optimal epsilon (Eps) value on DBSCAN algorithm to clustering data on peatland hotspots in Sumatra. IOP conference series: earth and environmental. Science. 2016;31:012012.","journal-title":"Science"},{"key":"77_CR16","unstructured":"Forbes G. The automatic detection of patterns in people\u2019s movements. Dissertation, University of Cape Town. 2002."},{"key":"77_CR17","doi-asserted-by":"crossref","unstructured":"Ng RT, Han J. CLARANS: A Method for Clustering Objects for Spatial Data Mining. In: IEEE Transactions on Knowledge and Data Engineering. 2002; 14(5).","DOI":"10.1109\/TKDE.2002.1033770"},{"key":"77_CR18","doi-asserted-by":"publisher","DOI":"10.1002\/9780470316801","author":"L Kaufman","year":"1990","unstructured":"Kaufman L, Rousseeuw PJ. Finding groups in data: an introduction to cluster analysis. Wiley. 1990. doi: 10.1002\/9780470316801 .","journal-title":"Wiley"},{"key":"77_CR19","unstructured":"Multiple linear regression- http:\/\/www.originlab.com\/doc\/Origin-Help\/Multi-Regression-Algorithm . Accessed 3 July 2017."},{"key":"77_CR20","unstructured":"Elbatta MNT. An improvement for DBSCAN algorithm for best results in varied densities. Dissertation, Gaza (PS): Islamic University of Gaza. 2012"},{"key":"77_CR21","unstructured":"Kirkl O, De La Iglesia B. Experimental evaluation of cluster quality measures. 2013. 978-1-4799-1568-2\/13. IEEE."},{"key":"77_CR22","unstructured":"Meila M (2003) Comparing clustering. In: Proceedings of COLT 2003."}],"container-title":["Journal of Big Data"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-017-0077-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s40537-017-0077-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-017-0077-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,28]],"date-time":"2019-09-28T09:18:42Z","timestamp":1569662322000},"score":1,"resource":{"primary":{"URL":"http:\/\/journalofbigdata.springeropen.com\/articles\/10.1186\/s40537-017-0077-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,5]]},"references-count":22,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["77"],"URL":"https:\/\/doi.org\/10.1186\/s40537-017-0077-4","relation":{},"ISSN":["2196-1115"],"issn-type":[{"value":"2196-1115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,7,5]]},"article-number":"20"}}