Exploiting domain knowledge to address class imbalance and a heterogeneous feature space in multi-class classification

IF 2.8 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Vldb Journal Pub Date : 2023-02-27 DOI:10.1007/s00778-023-00780-6
Vitali Hirsch, P. Reimann, Dennis Treder-Tschechlov, H. Schwarz, B. Mitschang
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利用领域知识解决多类分类中的类不平衡和异构特征空间
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来源期刊
Vldb Journal
Vldb Journal 工程技术-计算机:信息系统
CiteScore
12.30
自引率
4.80%
发文量
55
审稿时长
>12 weeks
期刊介绍: The journal is dedicated to the publication of scholarly contributions in areas of data management such as database system technology and information systems, including their architectures and applications. Further, the journal’s scope is restricted to areas of data management that are covered by the combined expertise of the journal’s editorial board. Submissions with a substantial theory component are welcome, but the VLDB Journal expects such submissions also to embody a systems component. In relation to data mining, the journal will handle submissions where systems issues play a significant role. Factors that we use to determine whether a data mining paper is within scope include: The submission targets systems issues in relation to data mining, e.g., by covering integration with a database engine or with other data management functionality. The submission’s contributions build on (rather than simply cite) work already published in database outlets, e.g., VLDBJ, ACM TODS, PVLDB, ACM SIGMOD, IEEE ICDE, EDBT. The journal''s editorial board has the necessary expertise on the submission''s topic. Traditional, stand-alone data mining papers that lack the above or similar characteristics are out of scope for this journal. Criteria similar to the above are applied to submission from other areas, e.g., information retrieval and geographical information systems.
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