{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T14:59:47Z","timestamp":1773673187488,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,31]],"date-time":"2021-12-31T00:00:00Z","timestamp":1640908800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71571162"],"award-info":[{"award-number":["71571162"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>At present, association rules have been widely used in prediction, personalized recommendation, risk analysis and other fields. However, it has been pointed out that the traditional framework to evaluate association rules, based on Support and Confidence as measures of importance and accuracy, has several drawbacks. Some papers presented several new evaluation methods; the most typical methods are Lift, Improvement, Validity, Conviction, Chi-square analysis, etc. Here, this paper first analyzes the advantages and disadvantages of common measurement indicators of association rules and then puts forward four new measure indicators (i.e., Bi-support, Bi-lift, Bi-improvement, and Bi-confidence) based on the analysis. At last, this paper proposes a novel Bi-directional interestingness measure framework to improve the traditional one. In conclusion, the bi-directional interestingness measure framework (Bi-support and Bi-confidence framework) is superior to the traditional ones in the aspects of the objective criterion, comprehensive definition, and practical application.<\/jats:p>","DOI":"10.3390\/axioms11010017","type":"journal-article","created":{"date-parts":[[2022,1,3]],"date-time":"2022-01-03T20:49:38Z","timestamp":1641242978000},"page":"17","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["An Improved Evaluation Methodology for Mining Association Rules"],"prefix":"10.3390","volume":"11","author":[{"given":"Fuguang","family":"Bao","sequence":"first","affiliation":[{"name":"Contemporary Business and Trade Research Center, Zhejiang Gongshang University, Hangzhou 310018, China"},{"name":"School of Management and E-business, Zhejiang Gongshang University, Hangzhou 310018, China"},{"name":"Academy of Zhejiang Culture Industry Innovation & Development, Zhejiang Gongshang University, Hangzhou 310018, China"}]},{"given":"Linghao","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Management and E-business, Zhejiang Gongshang University, Hangzhou 310018, China"}]},{"given":"Yiling","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Foreign Languages, Zhejiang Gongshang University, Hangzhou 310018, China"}]},{"given":"Cancan","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Management and E-business, Zhejiang Gongshang University, Hangzhou 310018, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9757-1915","authenticated-orcid":false,"given":"Chonghuan","family":"Xu","sequence":"additional","affiliation":[{"name":"Academy of Zhejiang Culture Industry Innovation & Development, Zhejiang Gongshang University, Hangzhou 310018, China"},{"name":"School of Business Administration, Zhejiang Gongshang University, Hangzhou 310018, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.knosys.2010.08.005","article-title":"A Soft Set Approach for Association Rules Mining","volume":"24","author":"Herawan","year":"2011","journal-title":"Knowl.-Based Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1007\/s42979-021-00725-2","article-title":"A Systematic Assessment of Numerical Association Rule Mining Methods","volume":"2","author":"Kaushik","year":"2021","journal-title":"SN Comput. Sci."},{"key":"ref_3","first-page":"750","article-title":"An improved association rule mining algorithm for large data","volume":"30","author":"Zhao","year":"2021","journal-title":"J. Intell. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.procs.2021.02.109","article-title":"Research on parallelization of Apriori algorithm in association rule mining","volume":"183","author":"Wang","year":"2021","journal-title":"Procedia Comput. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.ins.2020.02.073","article-title":"A survey of evolutionary computation for association rule mining","volume":"524","author":"Telikani","year":"2020","journal-title":"Inf. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1177\/0022002707308598","article-title":"A Tournament of Party Decision Rules","volume":"52","author":"Fowler","year":"1998","journal-title":"J. Confl. Resolut."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/978-981-16-0878-0_29","article-title":"An Association Mining Rules Implemented in Data Mining","volume":"225","author":"Varija","year":"2021","journal-title":"Smart Innov. Syst. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/S0167-739X(97)00019-8","article-title":"Mining generalized association rules","volume":"13","author":"Srikand","year":"1997","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2498\/cit.1002361","article-title":"Frequent Pattern-growth Algorithm on Multi-core CPU and GPU Processors","volume":"22","author":"Arour","year":"2014","journal-title":"J. Comput. Inf. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1177\/0165551507082271","article-title":"Incremental Maintenance of Generalized Association Rules under Taxonomy Evolution","volume":"34","author":"Tseng","year":"2008","journal-title":"J. Inf. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1515\/bsrj-2015-0008","article-title":"Data Mining as Support to Knowledge Management in Marketing","volume":"6","author":"Marijana","year":"2015","journal-title":"Bus. Syst. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1016\/j.eswa.2006.08.007","article-title":"Ranking Discovered Rules from Data Mining with Multiple Criteria by Data Envelopment Analysis","volume":"33","author":"Chen","year":"2007","journal-title":"Expert Syst. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"8503","DOI":"10.1016\/j.eswa.2008.10.038","article-title":"A New Method for Ranking Discovered Rules from Data Mining by DEA","volume":"36","author":"Toloo","year":"2009","journal-title":"Expert Syst. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1145\/1132960.1132963","article-title":"Interestingness Measures for Data Ming: A Survey","volume":"38","author":"Geng","year":"2006","journal-title":"ACM Comput. Surv."},{"key":"ref_15","first-page":"297","article-title":"A New Approach on Rare Association Rule Mining","volume":"53","author":"Hoque","year":"2012","journal-title":"Int. J. Comput. Appl."},{"key":"ref_16","first-page":"1","article-title":"Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm","volume":"1","author":"Zhang","year":"2013","journal-title":"Sci. World J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s12046-020-01380-8","article-title":"Distributed synthesized association mining for big transactional data","volume":"45","author":"Pal","year":"2020","journal-title":"Sadhana"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1142\/S0218488516500185","article-title":"An Efficient Approach for Incremental Mining Fuzzy Frequent Itemsets with FP-Tree","volume":"24","author":"Huo","year":"2016","journal-title":"Int. J. Uncertain. Fuzziness Knowl.-Based Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1002\/cta.2935","article-title":"An improved approach for mining association rules in parallel using Spark Streaming","volume":"49","author":"Liu","year":"2021","journal-title":"Int. J. Circuit Theory Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"120486","DOI":"10.1016\/j.techfore.2020.120486","article-title":"Discovering dynamic adverse behavior of policyholders in the life insurance industry","volume":"163","author":"Islam","year":"2021","journal-title":"Technol. Forecast. Soc. Change"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"19","DOI":"10.4018\/JOEUC.20210501.oa2","article-title":"Time-Aware CF and Temporal Association Rule-Based Personalized Hybrid Recommender System","volume":"33","author":"Yang","year":"2021","journal-title":"J. Organ. End User Comput."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Sanmiquel, L., Bascompta, M., Rossell, J.M., Anticoi, H.F., and Guash, E. (2018). Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques. Int. J. Environ. Res. Public Health, 15.","DOI":"10.20944\/preprints201801.0231.v1"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yu, W., Ma, X., Ogura, H., and Ye, D. (2021). Multi-Objective Optimization for High-Dimensional Maximal Frequent Itemset Mining. Appl. Sci., 11.","DOI":"10.3390\/app11198971"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.eswa.2017.02.024","article-title":"Predictability-based collective class association rule mining","volume":"79","author":"Song","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"681","DOI":"10.37727\/jkdas.2018.20.2.681","article-title":"A Proposal of Symmetrically Balanced Cross Entropy for Association Rule Evaluation","volume":"20","author":"Heechang","year":"2018","journal-title":"J. Korean Data Anal. Soc."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1007\/s11222-013-9404-6","article-title":"Evaluation and optimization of frequent, closed and maximal association rule based classification","volume":"24","author":"Shaharanee","year":"2014","journal-title":"Stat. Comput."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1023\/A:1009713703947","article-title":"Beyond Market Baskets: Generalizing Association Rules to Dependence Rules","volume":"2","author":"Silverstein","year":"1998","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_28","first-page":"277","article-title":"Research on Judgment Criterion of Association Rules","volume":"18","author":"Ma","year":"2003","journal-title":"Control. Decis."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Brin, S., Motwani, R., Ullman, J.D., and Tsur, S. (1997, January 11\u201315). Dynamic Itemset Counting and Implication Rules for Market Basket Data. Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, Tucson, AZ, USA.","DOI":"10.1145\/253260.253325"},{"key":"ref_30","first-page":"503","article-title":"A New Interestingness Measures for Ming Association Rules","volume":"30","author":"Li","year":"2011","journal-title":"J. China Soc. Sci. Tech. Inf."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Bao, F., Wu, Y., Li, Z., Li, Y., Liu, L., and Chen, G. (2020). Effect Improved for High-Dimensional and Unbalanced Data Anomaly Detection Model Based on KNN-SMOTE-LSTM. Complexity.","DOI":"10.1155\/2020\/9084704"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1016\/j.ejor.2006.10.059","article-title":"On Selecting Interestingness Measures for Association Rules: User Oriented Description and Multiple Criteria Decision Aid","volume":"184","author":"Lenca","year":"2008","journal-title":"Eur. J. Oper. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2015\/868634","article-title":"A Novel Method of Interestingness Measures for Association Rules Mining Based on Profit","volume":"1","author":"Ju","year":"2015","journal-title":"Discret. Dyn. Nat. Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/TKDE.2005.99","article-title":"Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions","volume":"17","author":"Adomavicius","year":"2005","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"483","DOI":"10.2147\/PRBM.S303239","article-title":"Understanding the Relationship Between Tourists\u2019 Consumption Behavior and Their Consumption Substitution Willingness Under Unusual Environment","volume":"14","author":"Xiang","year":"2021","journal-title":"Psychol. Res. Behav. Manag."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, J., Xu, C., and Liu, W. (Int. J. Mob. Commun., 2022). Understanding the adoption of mobile social payment? From the cognitive behavioral perspective, Int. J. Mob. Commun., in press.","DOI":"10.1504\/IJMC.2022.123794"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"101060","DOI":"10.1016\/j.elerap.2021.101060","article-title":"A novel POI recommendation method based on trust relationship and spatial-temporal factors","volume":"48","author":"Xu","year":"2021","journal-title":"Electron. Commer. Res. Appl."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Xu, C., Liu, D., and Mei, X. (2021). Exploring an Efficient POI Recommendation Model Based on User Characteristics and Spatial-Temporal Factors. Mathematics, 9.","DOI":"10.3390\/math9212673"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Tang, Z., Hu, H., and Xu, C. (2022). A federated learning method for network intrusion detection. Concurr. Comput. Pract. Exp., e6812.","DOI":"10.1002\/cpe.6812"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1504\/IJBIC.2020.108995","article-title":"A privacy-preserving recommendation method based on multi-objective optimisation for mobile users","volume":"16","author":"Xu","year":"2020","journal-title":"Int. J. Bio-Inspired Comput."},{"key":"ref_41","first-page":"1","article-title":"A Learning-Based POI Recommendation with Spatiotemporal Context Awareness","volume":"99","author":"Chen","year":"2020","journal-title":"IEEE Trans. Cybern"}],"container-title":["Axioms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1680\/11\/1\/17\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:56:51Z","timestamp":1760169411000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1680\/11\/1\/17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,31]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["axioms11010017"],"URL":"https:\/\/doi.org\/10.3390\/axioms11010017","relation":{},"ISSN":["2075-1680"],"issn-type":[{"value":"2075-1680","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,31]]}}}