{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:14:53Z","timestamp":1781108093331,"version":"3.54.1"},"reference-count":58,"publisher":"IGI Global Scientific Publishing","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,1,1]]},"abstract":"<p>The explosive growth and increasing complexity of the multimedia data have created a high demand of multimedia services and applications in various areas so that people can access and distribute the data easily. Unfortunately, traditional keyword-based information retrieval is no longer suitable. Instead, multimedia data mining and content-based multimedia information retrieval have become the key technologies in modern societies. Among many data mining techniques, association rule mining (ARM) is considered one of the most popular approaches to extract useful information from multimedia data in terms of relationships between variables. In this paper, a novel rule-based semantic concept classification framework using weighted association rule mining (WARM), capturing the significance degrees of the feature-value pairs to improve the applicability of ARM, is proposed to deal with major issues and challenges in large-scale video semantic concept classification. Unlike traditional ARM that the rules are generated by frequency count and the items existing in one rule are equally important, our proposed WARM algorithm utilizes multiple correspondence analysis (MCA) to explore the relationships among features and concepts and to signify different contributions of the features in rule generation. To the authors best knowledge, this is one of the first WARM-based classifiers in the field of multimedia concept retrieval. The experimental results on the benchmark TRECVID data demonstrate that the proposed framework is able to handle large-scale and imbalanced video data with promising classification and retrieval performance.<\/p>","DOI":"10.4018\/jmdem.2013010103","type":"journal-article","created":{"date-parts":[[2013,8,2]],"date-time":"2013-08-02T13:32:18Z","timestamp":1375450338000},"page":"46-67","source":"Crossref","is-referenced-by-count":5,"title":["Rule-Based Semantic Concept Classification from Large-Scale Video Collections"],"prefix":"10.4018","volume":"4","author":[{"given":"Lin","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mei-Ling","family":"Shyu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9209-390X","authenticated-orcid":true,"given":"Shu-Ching","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computing and Information Sciences, Florida International University, Miami, FL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jmdem.2013010103-0","doi-asserted-by":"crossref","unstructured":"Anwar, F., & Naftel, A. (2008). Video event modelling and association rule mining in multimedia surveillance systems. In Proceedings of the IEEE International Conference on Visual Information Engineering (pp. 426\u2013431).","DOI":"10.1049\/cp:20080351"},{"issue":"1","key":"jmdem.2013010103-1","first-page":"9250","article-title":"An application of Bayesian classification to interval encoded temporal mining with prioritized items.","volume":"3","author":"C.Balasubramanian","year":"2009","journal-title":"International Journal of Computer Science and Information Security"},{"key":"jmdem.2013010103-2","doi-asserted-by":"publisher","DOI":"10.1109\/MMUL.2010.4"},{"key":"jmdem.2013010103-3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2044508"},{"key":"jmdem.2013010103-4","doi-asserted-by":"crossref","unstructured":"Bouzouitz, I., & Elloumi, S. (2007). Integrated generic association rule based classifier. In Proceedings of the IEEE International Conference on Database and Expert Systems Applications (pp. 514\u2013518).","DOI":"10.1109\/DEXA.2007.145"},{"key":"jmdem.2013010103-5","doi-asserted-by":"crossref","unstructured":"Cai, C. H., Fu, A. W. C., Cheng, C. H., & Kwong, W. W. (1998). Mining association rules with weighted items. In Proceedings of the IEEE International Conference on Database Engineering and Applications Symposium (pp. 68\u201377).","DOI":"10.1109\/IDEAS.1998.694360"},{"key":"jmdem.2013010103-6","doi-asserted-by":"crossref","unstructured":"Chen, M., Chen, S.-C., & Shyu, M.-L. (2007). Hierarchical temporal association mining for video event detection in video databases. In Proceedings of the Second IEEE International Workshop on Multimedia Databases and Data Management (p. 137-145).","DOI":"10.1109\/ICDEW.2007.4400983"},{"key":"jmdem.2013010103-7","doi-asserted-by":"publisher","DOI":"10.1109\/69.553155"},{"key":"jmdem.2013010103-8","doi-asserted-by":"publisher","DOI":"10.4018\/jmdem.2010111201"},{"key":"jmdem.2013010103-9","first-page":"489","article-title":"A dynamic user concept pattern learning framework for content-based image retrieval.","volume":"36","author":"S.-C.Chen","year":"2006","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics"},{"key":"jmdem.2013010103-10","doi-asserted-by":"crossref","unstructured":"Chen, S.-C., Shyu, M.-L., & Chen, M. (2008). An effective multi-concept classifier for video streams. In Proceedings of the Second IEEE International Conference on Semantic Computing (pp. 80-87).","DOI":"10.1109\/ICSC.2008.72"},{"key":"jmdem.2013010103-11","doi-asserted-by":"publisher","DOI":"10.1504\/IJCAT.2006.012001"},{"key":"jmdem.2013010103-12","unstructured":"Chen, S.-C., Shyu, M.-L., Zhang, C., & Strickrott, J. (2001). Multimedia data mining for traffic video sequences. In Proceedings of the Second International Workshop on Multimedia Data Mining (78-85)."},{"key":"jmdem.2013010103-13","doi-asserted-by":"crossref","unstructured":"Chen, X., Zhang, C., Chen, S.-C., & Chen, M. (2005). A latent semantic indexing based method for solving multiple instance learning problem in region-based image retrieval. In Proceedings of the IEEE International Symposium on Multimedia (pp. 37-44).","DOI":"10.1109\/ISM.2005.10"},{"key":"jmdem.2013010103-14","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2008.2007257"},{"key":"jmdem.2013010103-15","doi-asserted-by":"publisher","DOI":"10.1145\/1348246.1348248"},{"key":"jmdem.2013010103-16","unstructured":"Fatemi, N., Poulin, F., Raileany, L. E., & Smeaton, A. F. (2009). Using association rule mining to enrich semantic concepts for video retrieval. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (pp. 6\u20138)."},{"key":"jmdem.2013010103-17","unstructured":"Fayyad, U. M., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery: An overview. In U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy (editors), Advances in Knowledge Discovery and Data Mining (pp. 1-34). AAAI\/MIT Press."},{"key":"jmdem.2013010103-18","doi-asserted-by":"crossref","unstructured":"Ge, J., Qiu, Y., Chen, Z., & Yin, S. (2008). Technology of information push based on weighted association rules mining. In Proceedings of the IEEE International Conference on Fuzzy Systems and Knowledge Discovery (pp. 615\u2013619).","DOI":"10.1109\/FSKD.2008.158"},{"key":"jmdem.2013010103-19","doi-asserted-by":"crossref","unstructured":"Glotin, H., Zhao, Z.-Q., Gao, J., & Wu, X. (2010). A matrix modular SVM robust to imbalanced data for efficient visual concept detection. In Proceedings of the ACM International Conference on Multimedia Information Retrieval (pp. 333\u2013338).","DOI":"10.1145\/1743384.1743439"},{"key":"jmdem.2013010103-20","doi-asserted-by":"publisher","DOI":"10.5121\/ijma.2011.3110"},{"key":"jmdem.2013010103-21","unstructured":"Huang, X., Chen, S.-C., Shyu, M.-L., & Zhang, C. (2002). User concept pattern discovery using relevance feedback and multiple instance learning for content-based image retrieval. In Proceedings of the Third International Workshop on Multimedia Data Mining (pp. 100-108)."},{"key":"jmdem.2013010103-22","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2009.2036235"},{"key":"jmdem.2013010103-23","doi-asserted-by":"crossref","unstructured":"Kleban, J., Xie, X., & Ma, W.-Y. (2008). Spatial pyramid mining for logo detection in natural scenes. In Proceedings of the IEEE International Conference on Multimedia and Expo (pp. 1077-1080).","DOI":"10.1109\/ICME.2008.4607625"},{"key":"jmdem.2013010103-24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-30220-6_4"},{"key":"jmdem.2013010103-25","author":"D. T.Larose","year":"2005","journal-title":"Discovering knowledge in data"},{"issue":"1","key":"jmdem.2013010103-26","first-page":"1","article-title":"Content-based multimedia information retrieval: State of art and challenges. ACM Transactions on Multimedia Computing","volume":"2","author":"M. S.Lew","year":"2006","journal-title":"Communications and Applications"},{"key":"jmdem.2013010103-27","doi-asserted-by":"publisher","DOI":"10.1109\/MMUL.2011.35"},{"key":"jmdem.2013010103-28","doi-asserted-by":"crossref","unstructured":"Lin, L., Ravitz, G., Shyu, M.-L., & Chen, S.-C. (2007). Video semantic concept discovery using multimodal-based association classification. In Proceedings of the IEEE International Conference on Multimedia & Expo (pp. 859-862).","DOI":"10.1109\/ICME.2007.4284786"},{"key":"jmdem.2013010103-29","doi-asserted-by":"crossref","unstructured":"Lin, L., Ravitz, G., Shyu, M.-L., & Chen, S.-C. (2008). Correlation-based video semantic concept detection using multiple correspondence analysis. In Proceedings of the IEEE International Symposium on Multimedia (pp. 316-321).","DOI":"10.1109\/ISM.2008.111"},{"key":"jmdem.2013010103-30","doi-asserted-by":"publisher","DOI":"10.1142\/S1793351X09000860"},{"key":"jmdem.2013010103-31","doi-asserted-by":"publisher","DOI":"10.4018\/jmdem.2010111203"},{"key":"jmdem.2013010103-32","doi-asserted-by":"publisher","DOI":"10.4018\/jmdem.2010100105"},{"key":"jmdem.2013010103-33","doi-asserted-by":"crossref","unstructured":"Lin, L., Shyu, M.-L., & Chen, S.-C. (2009). Correlation-based interestingness measure for video semantic concept detection. In Proceedings of the 2009 IEEE International Conference on Information Reuse and Integration (pp. 120-125).","DOI":"10.1109\/IRI.2009.5211537"},{"key":"jmdem.2013010103-34","doi-asserted-by":"crossref","unstructured":"Lin, L., Shyu, M.-L., Ravitz, G., & Chen, S.-C. (2009). Video semantic concept detection via associative classification. In Proceedings of the 10th IEEE International Conference on Multimedia and Expo (pp. 418-421).","DOI":"10.1109\/ICME.2009.5202523"},{"key":"jmdem.2013010103-35","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2007.911826"},{"key":"jmdem.2013010103-36","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2012.07.001"},{"key":"jmdem.2013010103-37","doi-asserted-by":"crossref","unstructured":"Perko, R., Paletta, L., & Leonardis, A. (2009). Learning contextual rules for priming object categories in images. In Proceedings of the IEEE International Conference on Image Processing (pp. 1429\u20131432).","DOI":"10.1109\/ICIP.2009.5414633"},{"key":"jmdem.2013010103-38","first-page":"247","article-title":"Weighted support association rule mining using closed itemset lattices in parallel.","volume":"9","author":"A. M. Z.Rahman","year":"2009","journal-title":"International Journal of Computer Science and Network Security"},{"key":"jmdem.2013010103-39","doi-asserted-by":"crossref","unstructured":"Shyu, M.-L., Chen, S.-C., Chen, M., & Zhang, C. (2004). A unified framework for image database clustering and content-based retrieval. In Proceedings of the Second ACM International Workshop on Multimedia Databases (pp. 19-27).","DOI":"10.1145\/1032604.1032609"},{"key":"jmdem.2013010103-40","doi-asserted-by":"crossref","unstructured":"Shyu, M.-L., Chen, S.-C., Chen, M., Zhang, C., & Sarinnapakorn, K. (2003). Image database retrieval utilizing affinity relationships. In Proceedings of the First ACM International Workshop on Multimedia Databases (pp. 78-85).","DOI":"10.1145\/951676.951691"},{"issue":"3","key":"jmdem.2013010103-41","first-page":"319","article-title":"Generalized affinity-based association rule mining for multimedia database queries. Knowledge and Information Systems (KAIS)","volume":"3","author":"M.-L.Shyu","year":"2001","journal-title":"International Journal (Toronto, Ont.)"},{"key":"jmdem.2013010103-42","first-page":"2035","article-title":"Stochastic clustering for organizing distributed information source. IEEE Transactions on Systems, Man, and Cybernetics","volume":"34","author":"M.-L.Shyu","year":"2004","journal-title":"Part B"},{"key":"jmdem.2013010103-43","doi-asserted-by":"publisher","DOI":"10.1142\/S1793351X07000044"},{"key":"jmdem.2013010103-44","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2007.911830"},{"key":"jmdem.2013010103-45","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-76569-3_6"},{"key":"jmdem.2013010103-46","doi-asserted-by":"publisher","DOI":"10.1561\/1500000014"},{"key":"jmdem.2013010103-47","doi-asserted-by":"publisher","DOI":"10.5120\/821-1163"},{"key":"jmdem.2013010103-48","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2007.190723"},{"key":"jmdem.2013010103-49","doi-asserted-by":"crossref","unstructured":"Tao, F., Murtagh, F., & Farid, M. (2003). Weighted association rule mining using weighted support and significance framework. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 661\u2013666).","DOI":"10.1145\/956750.956836"},{"key":"jmdem.2013010103-50","doi-asserted-by":"publisher","DOI":"10.5121\/ijma.2011.3405"},{"issue":"1","key":"jmdem.2013010103-51","first-page":"1","article-title":"Association rule mining based video classifier with late acceptance hill climbing approach.","volume":"48","author":"V.Vijayakumar","year":"2013","journal-title":"Journal of Theoretical and Applied Information Technology"},{"key":"jmdem.2013010103-52","doi-asserted-by":"crossref","unstructured":"Wang, W., Yang, J., & Yu, P. (2000). Efficient mining of weighted association rules (WAR). In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 270\u2013274).","DOI":"10.1145\/347090.347149"},{"key":"jmdem.2013010103-53","doi-asserted-by":"crossref","unstructured":"Wang, Y. J., Zheng, X., Coenen, F., & Li, C. Y. (2008). Mining allocating patterns in one-sum weighted items. In Proceedings of the IEEE International Conference on Data Mining Workshops (pp. 592\u2013598).","DOI":"10.1109\/ICDMW.2008.112"},{"key":"jmdem.2013010103-54","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.187"},{"key":"jmdem.2013010103-55","doi-asserted-by":"crossref","unstructured":"Witten, I. H., Frank, E., & Hall, Mark A. (2011). Data mining: Practical machine learning tools and techniques (3rd ed.). San Francisco, CA: Morgan Kaufmann.","DOI":"10.1016\/B978-0-12-374856-0.00001-8"},{"key":"jmdem.2013010103-56","unstructured":"Yanagawa, A., Chang, S.-F., Kennedy, L., & Hsu, W. (2007). Columbia university\u2019s baseline detectors for 374 lscom semantic visual concepts. In Columbia University ADVENT Technical Report 222-2006-8."},{"key":"jmdem.2013010103-57","unstructured":"Zhang, C., Chen, X., Chen, M., Chen, S.-C., & Shyu, M.-L. (2005). A multiple instance learning approach for content based image retrieval using one-class support vector machine. In Proceedings of the IEEE International Conference on Multimedia & Expo (pp. 1142-1145)."}],"container-title":["International Journal of Multimedia Data Engineering and Management"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=78747","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T20:36:28Z","timestamp":1654115788000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jmdem.2013010103"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2013,1,1]]},"references-count":58,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2013,1]]}},"URL":"https:\/\/doi.org\/10.4018\/jmdem.2013010103","relation":{},"ISSN":["1947-8534","1947-8542"],"issn-type":[{"value":"1947-8534","type":"print"},{"value":"1947-8542","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,1,1]]}}}