{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T06:39:52Z","timestamp":1757313592771},"reference-count":17,"publisher":"IGI Global","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<p>Clustering is employed in various fields. However, the conventional method does not consider changing data. Therefore, if the data is changed, the entire dataset must be re-clustered. This article proposes a clustering method to update the clustering result obtained by a hierarchical clustering method without re-clustering when a point is inserted. This article defines the center and the radius of a cluster and determine the cluster to be inserted. The insertion location is determined by similarity based on the conventional clustering method. this research introduces the concept of outliers and consider creating a cluster caused by the insertion. By examining the multimodality of a cluster, the cluster is divided. In addition, when the number of clusters increases, data points previously inserted are updated by re-insertion. Compared with the conventional method, the experimental results demonstrate that the execution time of the proposed method is significantly smaller and clustering accuracy is comparable for some data.<\/p>","DOI":"10.4018\/ijsi.2020040101","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T19:52:12Z","timestamp":1581105132000},"page":"1-22","source":"Crossref","is-referenced-by-count":3,"title":["Incremental Hierarchical Clustering for Data Insertion and Its Evaluation"],"prefix":"10.4018","volume":"8","author":[{"given":"Kakeru","family":"Narita","sequence":"first","affiliation":[{"name":"Kyoto Institute of Technology, Kyoto, Japan"}]},{"given":"Teruhisa","family":"Hochin","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science, Kyoto Institute of Technology, Kyoto, Japan"}]},{"given":"Yoshihiro","family":"Hayashi","sequence":"additional","affiliation":[{"name":"Nitto Seiko Co., LTD., Kyoto, Japan"}]},{"given":"Hiroki","family":"Nomiya","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science, Kyoto Institute of Technology, Kyoto, Japan"}]}],"member":"2432","reference":[{"key":"IJSI.2020040101-0","doi-asserted-by":"publisher","DOI":"10.1145\/1951365.1951432"},{"key":"IJSI.2020040101-1","doi-asserted-by":"publisher","DOI":"10.1145\/130226.134466"},{"key":"IJSI.2020040101-2","doi-asserted-by":"publisher","DOI":"10.1137\/S0097539702418498"},{"key":"IJSI.2020040101-3","author":"D.Dua","year":"2019","journal-title":"UCI Machine Learning Repository"},{"key":"IJSI.2020040101-4","unstructured":"Ester, M., Kriegel, H. P., Sander, J., Wimmer, M., & Xu, X. (1998). Incremental clustering for mining in a data warehousing environment. Proceedings of the 24th International Conference on Very Large Data Bases, VLDB \u201998, San Francisco, CA (pp. 323\u2013333). Academic Press."},{"key":"IJSI.2020040101-5","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2013.01.010"},{"issue":"5","key":"IJSI.2020040101-6","first-page":"97","article-title":"An efficient incremental clustering algorithm.","volume":"3","author":"N.Gupta","year":"2013","journal-title":"World of Computer Science and Information Technology Journal"},{"key":"IJSI.2020040101-7","doi-asserted-by":"publisher","DOI":"10.5220\/0001857103000304"},{"key":"IJSI.2020040101-8","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176346577"},{"key":"IJSI.2020040101-9","doi-asserted-by":"publisher","DOI":"10.1080\/0951192X.2013.874595"},{"key":"IJSI.2020040101-10","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1963.10500845"},{"key":"IJSI.2020040101-11","doi-asserted-by":"publisher","DOI":"10.1016\/j.bushor.2015.03.008"},{"key":"IJSI.2020040101-12","author":"S.Marsland","year":"2009","journal-title":"Machine Learning: An Algorithmic Perspective"},{"key":"IJSI.2020040101-13","doi-asserted-by":"crossref","unstructured":"Narita, K., Hochin, T., Hayashi, Y., & Nomiya, H. (2019). Improvement of incremental hierarchical clustering algorithm by re-insertion. Proceedings of the 6th International Conference on Computational Science\/ Intelligence and Applied Informatics (CSII 2019). Academic Press.","DOI":"10.1007\/978-3-030-25225-0_8"},{"key":"IJSI.2020040101-14","doi-asserted-by":"publisher","DOI":"10.1109\/CSII.2018.00025"},{"key":"IJSI.2020040101-15","unstructured":"Ribert, A., Ennaji, A., & Lecourtier, Y. (1999). An incremental hierarchical clustering. Proceedings of 1999 Vision Interface Conference (pp. 586\u2013591). Academic Press."},{"key":"IJSI.2020040101-16","author":"N.Zumel","year":"2014","journal-title":"Practical data science with R"}],"container-title":["International Journal of Software Innovation"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=248527","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T21:09:32Z","timestamp":1651871372000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJSI.2020040101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2020,4,1]]},"references-count":17,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,4]]}},"URL":"https:\/\/doi.org\/10.4018\/ijsi.2020040101","relation":{},"ISSN":["2166-7160","2166-7179"],"issn-type":[{"value":"2166-7160","type":"print"},{"value":"2166-7179","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,1]]}}}