{"title":"使用比较的交互式方法来引出用户偏好","authors":"Jianfeng Zhang, Weihong Han, Yan Jia, Peng Zou","doi":"10.1109/ICCIS.2012.178","DOIUrl":null,"url":null,"abstract":"The complexity of today's networks and distributed systems makes the process of network monitoring difficult. The amount of data produced by many distributed security tools can be overwhelming. So it's very difficult and limited to get the most risky alert through manual process based on the huge network alerts with many attributes, such as asset, priority, reliability, risk, type et al. The common method used to rank the alerts is scoring function, the higher the score, the more risky of the alert. Our motivation is that many times user can not precisely specify the weights for the scoring function as their preference in order to produce the preferred order of results. In this paper, we propose a new interactive preference searching method to elicit user's preference. An extensive performance study using both synthetic and real datasets is reported to verify its effectiveness and efficiency.","PeriodicalId":269967,"journal":{"name":"2012 Fourth International Conference on Computational and Information Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interactive Approach to Eliciting Users' Preference Using Comparisons\",\"authors\":\"Jianfeng Zhang, Weihong Han, Yan Jia, Peng Zou\",\"doi\":\"10.1109/ICCIS.2012.178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The complexity of today's networks and distributed systems makes the process of network monitoring difficult. The amount of data produced by many distributed security tools can be overwhelming. So it's very difficult and limited to get the most risky alert through manual process based on the huge network alerts with many attributes, such as asset, priority, reliability, risk, type et al. The common method used to rank the alerts is scoring function, the higher the score, the more risky of the alert. Our motivation is that many times user can not precisely specify the weights for the scoring function as their preference in order to produce the preferred order of results. In this paper, we propose a new interactive preference searching method to elicit user's preference. An extensive performance study using both synthetic and real datasets is reported to verify its effectiveness and efficiency.\",\"PeriodicalId\":269967,\"journal\":{\"name\":\"2012 Fourth International Conference on Computational and Information Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Conference on Computational and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIS.2012.178\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Conference on Computational and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2012.178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interactive Approach to Eliciting Users' Preference Using Comparisons
The complexity of today's networks and distributed systems makes the process of network monitoring difficult. The amount of data produced by many distributed security tools can be overwhelming. So it's very difficult and limited to get the most risky alert through manual process based on the huge network alerts with many attributes, such as asset, priority, reliability, risk, type et al. The common method used to rank the alerts is scoring function, the higher the score, the more risky of the alert. Our motivation is that many times user can not precisely specify the weights for the scoring function as their preference in order to produce the preferred order of results. In this paper, we propose a new interactive preference searching method to elicit user's preference. An extensive performance study using both synthetic and real datasets is reported to verify its effectiveness and efficiency.