S. Mariana, I. Surjandari, Arian Dhini, Asma Rosyidah, P. Prameswari
{"title":"基于关联规则挖掘的在线公共目录图书推荐系统构建","authors":"S. Mariana, I. Surjandari, Arian Dhini, Asma Rosyidah, P. Prameswari","doi":"10.1109/ICSITECH.2017.8257119","DOIUrl":null,"url":null,"abstract":"Improvement in service quality in Online Public Access Catalog (OPAC) of Universitas Indonesia's library is required due to its increasing use. Book recommendation system is one of the efforts that is conducted by Universitas Indonesia to improve it by providing related books the user may need. Thus, it is required to know how the books correlation is. This research uses data mining to process numerous data by using association analysis in loan records. It is able to find interesting relationship in a large set of data. In this research, there are two approaches in association analysis used to mine the association rules namely frequent itemset mining and infrequent itemset mining. Each approach is applied through an algorithm and both have showed its own results. Then, these results are evaluated and compared to find best rules to be input of book recommendation system.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Association rule mining for building book recommendation system in online public access catalog\",\"authors\":\"S. Mariana, I. Surjandari, Arian Dhini, Asma Rosyidah, P. Prameswari\",\"doi\":\"10.1109/ICSITECH.2017.8257119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Improvement in service quality in Online Public Access Catalog (OPAC) of Universitas Indonesia's library is required due to its increasing use. Book recommendation system is one of the efforts that is conducted by Universitas Indonesia to improve it by providing related books the user may need. Thus, it is required to know how the books correlation is. This research uses data mining to process numerous data by using association analysis in loan records. It is able to find interesting relationship in a large set of data. In this research, there are two approaches in association analysis used to mine the association rules namely frequent itemset mining and infrequent itemset mining. Each approach is applied through an algorithm and both have showed its own results. Then, these results are evaluated and compared to find best rules to be input of book recommendation system.\",\"PeriodicalId\":165045,\"journal\":{\"name\":\"2017 3rd International Conference on Science in Information Technology (ICSITech)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 3rd International Conference on Science in Information Technology (ICSITech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSITECH.2017.8257119\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Science in Information Technology (ICSITech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSITECH.2017.8257119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Association rule mining for building book recommendation system in online public access catalog
Improvement in service quality in Online Public Access Catalog (OPAC) of Universitas Indonesia's library is required due to its increasing use. Book recommendation system is one of the efforts that is conducted by Universitas Indonesia to improve it by providing related books the user may need. Thus, it is required to know how the books correlation is. This research uses data mining to process numerous data by using association analysis in loan records. It is able to find interesting relationship in a large set of data. In this research, there are two approaches in association analysis used to mine the association rules namely frequent itemset mining and infrequent itemset mining. Each approach is applied through an algorithm and both have showed its own results. Then, these results are evaluated and compared to find best rules to be input of book recommendation system.