{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T14:57:08Z","timestamp":1781103428811,"version":"3.54.1"},"reference-count":24,"publisher":"IGI Global Scientific Publishing","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4]]},"abstract":"<jats:p>Popular data mining methods support knowledge discovery from patterns that hold in relations. For many applications, it is difficult to find strong associations among data items at low or primitive levels of abstraction. Mining association rules at multiple levels may lead to more informative and refined knowledge from data. Multi-level association rule mining is a variation of association rule mining for finding relationships between items at each level by applying different thresholds at different levels. In this study, an inventory classification policy is provided. At each level, the loss profit of frequent items is determined. The obtained loss profit is used to rank frequent items at each level with respect to their category, content and brand. This helps inventory manager to determine the most profitable item with respect to their category, content and brand. An example is illustrated to validate the results. Further, to comprehend the impact of above approach in the real scenario, experiments are conducted on the exiting dataset.<\/jats:p>","DOI":"10.4018\/ijdsst.2019040101","type":"journal-article","created":{"date-parts":[[2019,2,13]],"date-time":"2019-02-13T10:17:51Z","timestamp":1550053071000},"page":"1-12","source":"Crossref","is-referenced-by-count":21,"title":["Inventory Classification Using Multi-Level Association Rule Mining"],"prefix":"10.4018","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7106-6141","authenticated-orcid":true,"given":"Reshu","family":"Agarwal","sequence":"first","affiliation":[{"name":"G L Bajaj Institute of Technology and Management, Greater Noida, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7501-6571","authenticated-orcid":true,"given":"Mandeep","family":"Mittal","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Amity Institute of Applied Sciences, Amity University, Noida, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJDSST.2019040101-0","doi-asserted-by":"publisher","DOI":"10.4018\/IJBAN.2016010103"},{"key":"IJDSST.2019040101-1","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-4666-9888-8.ch012"},{"key":"IJDSST.2019040101-2","doi-asserted-by":"publisher","DOI":"10.1145\/170035.170072"},{"key":"IJDSST.2019040101-3","unstructured":"Agrawal, R., & Srikant, R. (1994). Fast algorithm for mining association rules. In Proceedings of the 20th International Conference on Very Large Data Bases, Chile (pp. 487-499)."},{"key":"IJDSST.2019040101-4","unstructured":"Anand, S. S., Hughes, J. G., Bell, D. A., & Patrick, A. R. (1997). Tackling the cross-sales problem using data mining. In Proceedings of the 2nd Pacific-Asia Conference on Knowledge Discovery & Data Mining, Hong Kong (pp. 331-343)."},{"issue":"2","key":"IJDSST.2019040101-5","first-page":"75","article-title":"Identification of purchase dependencies in retail sale.","volume":"8","author":"P. K.Bala","year":"2008","journal-title":"International Journal of Strategic Management"},{"key":"IJDSST.2019040101-6","doi-asserted-by":"publisher","DOI":"10.5120\/4648-6722"},{"key":"IJDSST.2019040101-7","doi-asserted-by":"publisher","DOI":"10.1080\/09537280903326578"},{"key":"IJDSST.2019040101-8","doi-asserted-by":"publisher","DOI":"10.1145\/312129.312241"},{"key":"IJDSST.2019040101-9","doi-asserted-by":"publisher","DOI":"10.1145\/347090.347156"},{"key":"IJDSST.2019040101-10","first-page":"3293","article-title":"Genetic algorithm for item selection with cross-selling considerations.","author":"Y.Cheng","year":"2005","journal-title":"Proceedings of the 4th International Conference on Machine Learning and Cybernetics"},{"key":"IJDSST.2019040101-11","doi-asserted-by":"publisher","DOI":"10.1108\/eb054765"},{"key":"IJDSST.2019040101-12","doi-asserted-by":"publisher","DOI":"10.1016\/0272-6963(87)90008-8"},{"key":"IJDSST.2019040101-13","first-page":"420","article-title":"Discovery of multiple-level association rules from large databases","author":"J.Han","year":"1995","journal-title":"Proceedings of the 21st Very Large Data Bases Conference"},{"key":"IJDSST.2019040101-14","doi-asserted-by":"publisher","DOI":"10.1504\/IJSSCI.2008.019609"},{"key":"IJDSST.2019040101-15","first-page":"225","article-title":"Mining multi-cross-level fuzzy weighted association rules","author":"M.Kaya","year":"2004","journal-title":"Proceedings of 2nd IEEE International Conference on Intelligent Systems"},{"key":"IJDSST.2019040101-16","doi-asserted-by":"publisher","DOI":"10.5267\/j.msl.2015.1.004"},{"key":"IJDSST.2019040101-17","doi-asserted-by":"publisher","DOI":"10.1504\/IJDS.2015.072419"},{"key":"IJDSST.2019040101-18","doi-asserted-by":"publisher","DOI":"10.1109\/TENCON.2003.1273266"},{"key":"IJDSST.2019040101-19","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2004.07.014"},{"key":"IJDSST.2019040101-20","unstructured":"Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory management & production planning & scheduling (3rd ed.). John Wiley & Sons, Inc."},{"key":"IJDSST.2019040101-21","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2003.1250942"},{"key":"IJDSST.2019040101-22","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-005-1359-6"},{"key":"IJDSST.2019040101-23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.01.127"}],"container-title":["International Journal of Decision Support System Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=223424","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T06:04:53Z","timestamp":1651817093000},"score":1,"resource":{"primary":{"URL":"http:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJDSST.2019040101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2019,4]]},"references-count":24,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.4018\/ijdsst.2019040101","relation":{},"ISSN":["1941-6296","1941-630X"],"issn-type":[{"value":"1941-6296","type":"print"},{"value":"1941-630X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4]]}}}